Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://www.youtube.com/watch?v=-NZbXGoj2bQ Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://youtu.be/eHIlY01n5LI Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://www.youtube.com/watch?v=xWugtCTnWbw Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://www.youtube.com/watch?v=D5QCcfi7acc Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://youtu.be/6YN5p6T7vys Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://www.youtube.com/watch?v=CDBrPdh4Jw&abchannel=HarpreetSahota%7CTheArtistsofDataScience Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://www.youtube.com/watch?v=bFy64aMh_ho Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://youtu.be/NDVD28raDqw Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://www.youtube.com/watch?v=G78EE7P-EV8 Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://www.youtube.com/watch?v=KE_i6puujLo Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://youtu.be/zn0XHbXrhjs Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://youtu.be/wVsszZLrl6g Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://youtu.be/uYWKVCdNjPk Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://www.youtube.com/watch?v=Wt0w92QYIPg Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://youtu.be/idD5TyW45y8 Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://www.youtube.com/watch?v=jwi9WH7588E Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://www.youtube.com/watch?v=9nSil9d9f7w&ab_channel=HarpreetSahota%7CTheArtistsofDataScience Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://www.youtube.com/watch?v=KUEpn6uiapM Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Find Daliana onine: https://www.linkedin.com/today/author/dalianaliu Watch the video of this episode: https://youtu.be/ldXGeOjGkx4 Memorable Quotes from the Episode: [00:37:10] "Whatever we can do to actually, like, connect to our fellow man and woman is really, really important. And exercise and activity is a big way to do that. And the community serves our mental health. Whether you're an introvert or an extrovert, it doesn't really matter. Being around people serves you and allows you to feel like you're part of something like a belonging, right? So I think in all those ways, activity and exercise is huge for individuals who are just really trying to establish a baseline of mental health." Highlights of the show: [00:00:09] Guest Introduction [00:02:05] Where you grew up and what it was like there? [00:04:19] When you were in high school, what did you think your future would look like? [00:07:41] How did you gravitate towards math having this interest that seemed a bit like honestly, like artsy kind of interest. Did you see any kind of art in mathematics? Is that what drew you to it? What was that pool? [00:12:05] How is writing been an important element of success in your career? [00:15:58 How do you suggest people get better at writing? Is it just going through, like a business writing class, one of those free business writing classes? How did you get developed that skill? [00:20:49] What are some other critical elements to success for someone's career as a data scientist that don't get taught in school? [00:24:34] How did you learn different skills? [00:27:10] I'm wondering if a little bit in there is that feeling of imposter syndrome, a feeling of not wanting to ask a question because you don't want to be perceived as not knowing something like, oh, you're supposed to be a data scientist. Don't you know how to do this? Do you notice this happening a lot with with data scientist of any career level? [00:30:53] Let's talk about how your day to day work as a data scientist is. How is this different from what you expected it to be when you were an aspiring data scientist? [00:35:23] What what do most data scientists do wrong when it comes to their career development? [00:38:35] Where would you draw the line between a data analyst and a data scientist? Can you point to one skill and be like, oh, right there, that's it. If only you knew this one thing, you'd be a data scientist. Does it work like that? What are your thoughts on that? [00:44:09] What are your thoughts on why people are giving you so much pushback around that particular thing? [00:52:24] How do you try to ensure that you're providing as fresh a perspective as possible with the content that you create? [00:53:33] What are your thoughts on what it means to be a data science influencer? [00:55:19] Let get into your podcast "the data scientist show". Talk to us about that. How did that idea come into your mind that you want to start a podcast? Who should listen to this podcast? Do you have to be experienced in the game to listen to it? Or is this a broad spectrum of data scientists. [01:00:07-01:00:15] Let's talk about your experience being a woman in tech and a woman in data.If you have any advice or words of encouragement for the women in our audience who are breaking into or currently in our data world? [01:06:05] What can we do to foster the inclusion of women in data science and AI? [01:05:07] It is 100 years in the future. What do you want to be remembered for? Random Round [01:07:12] In your opinion, what do most people think within the first few seconds of meeting you for the first time? [01:07:41] You do like journaling in the morning or anything like that? [01:07:57] What are you currently reading? [01:08:42] Can you share just a couple of tips on how not to feel bad not finishing a book? [01:10:21] Pirates are ninjas? [01:10:31] Mountains or ocean? [01:10:38] If you were a vegetable, what vegetable would you be? [01:10:48] If you could live in a book, TV show or movie, what would it be? -- Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://www.youtube.com/watch?v=BltSMpwSBWw Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Find Lara online: https://www.drlarapence.com/ Watch the video of this episode: https://www.youtube.com/watch?v=jKwGLkMvzis Memorable Quotes from the Episode: [00:38:09] "Whatever we can do to actually, like, connect to our fellow man and woman is really, really important. And exercise and activity is a big way to do that. And the community serves our mental health. Whether you're an introvert or an extrovert, it doesn't really matter. Being around people serves you and allows you to feel like you're part of something like a belonging, right? So I think in all those ways, activity and exercise is huge for individuals who are just really trying to establish a baseline of mental health." Highlights of the show: [00:01:31] Guest Introduction [00:03:03] Where you grew up and what it was like there? [00:04:56] Did you think you're going to be into when you're in high school? [00:06:36] It's fascinating that you love to study humans because we are interesting, interesting creatures.We always like to compare ourselves to others. So what is it? What is it about humans that make us always go through this, this comparison thing? [00:09:13] If somebody else is talking the same topics that I'm talking about and they've got a bigger audience, if anything, they're attracting more people to it. So it's just this little mindset shift. Can we work through my comparison issues on the air? Is that something you want to explore with a couple of questions? [00:13:13] Speaking to my audience, a lot of them are are definitely future leaders, if not already current leaders. It may include senior level management type of level, things like that. As we move up the chain in responsibility it can get tempting for us to take on more and more responsibilities, right? [00:13:31] At some point we need to start saying no, but how? How do we go about saying no? Why is it important that we are able to say no? [00:17:17] "Busy calendar and a busy mind will destroy your ability to do great things in the world." [00:19:02] Decision making is definitely an important aspect of data science, especially at the leadership level. You've got to make decisions, you've got to make them well because the consequences could cost in many different ways. I wonder if you can share some ways for us to improve our decision making process. [00:22:58] Let's talk about self-awareness as it relates to coming up with our values. First, how do we describe self-awareness in this context? How can we use that to help us identify our values? [00:26:37] Is there something that we can attest that we can give ourselves to determine just how self-aware we actually are? [00:29:33] What is this concept of of a personal true north? Talk to us about this this concept and how do we define that for ourselves? [00:31:27] What are some surefire ways that that we can use to make sure that we can avoid distraction and stay productive? [00:35:55] There's an interesting connection between movement and mental health, if you just talk to us a little bit about that. [00:39:49] How do we fight that urge and force ourselves to get that movement in because it's going to help us in the long term, right? [00:44:01] Talking about your obsession with curiosity. What do you find so curious about curiosity? [00:46:31] "I don't need anyone's permission to be curious either. It's free." [00:46:44] What can I do to ensure that I don't do anything that would cause him (Harpreet's son) to lose that curiosity? [00:49:21] How do we cultivate that sense of curiosity as adults? [00:51:24] It is 100 years in the future. What do you want to be remembered for? Random Round [00:52:11] What are you most active with in terms of podcasting? [00:53:06] What is the the life box substance about this? [00:54:46] What in your opinion, what do you think people think within the first few seconds of meeting you for the first time? [00:55:11] What are you currently reading? [00:55:31] What song do you have on repeat? [00:55:54] What accomplishment are you most proud of? [00:56:26] What sport are you playing? [00:56:31] What makes you cry? [00:57:14] What is your favorite city? [00:57:50] What is something you can never seem to finish? -- Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://www.youtube.com/watch?v=NstXQM0M5JI&t=5s Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Find Jonathan online: https://www.linkedin.com/in/jonathan-wonsulting/ Find Jerry Lee online: https://www.linkedin.com/in/jehakjerrylee/ Watch the video of this episode: https://www.youtube.com/watch?v=KdfFyY_-XT8&t=89s Memorable Quotes from the Episode: [00:26:43] " I think one of the best things about the content is that we sort of have seen on LinkedIn, Austin, Balzac as an example, he posts very, very actionable content and that's very much what we sort of like to strive for as well when we talk about job search, making it extremely tangible so that someone who is reading it can take action that very second. So for you, if just content that you really like and enjoy with and enjoyed and you're like, Listen, I'm going to try it. If it takes you less than 5 minutes, do it. Try it. Best case scenario is that you get a job out of it. The worst case scenario, you use 5 minutes." Highlights of the show: [00:00:41] Guests Introduction [00:03:41] Jerry, talk to us about where you grew up and what it was like there? [00:05:18] Jonathan Mann, tell us a little bit about yourself. Where did you grow up and what it was like there? [00:06:49] How do you guys know each other? These guys grow up together. You guys go to high school together. You know, what's what's the back story there? [00:07:55] Talk to us first about the genesis of the company. How did this idea start? How did this idea come about? What were you seeing in the world that was just like I just just couldn't take anymore. You had to do something about it. Like, what was that moment? [00:10:49] So Jonathan talks about 'what is the definition of an underdog' . Who are the underdogs? And then maybe after that, Jerry, why is it that companies tend to overlook people just because of their "pedigree"? [00:12:25] What is it about these companies overlooking people just because of their pedigree? [00:14:50] What's like one of the first few things that you start to do with people? What are the first, I guess, myths you start to debunk or the mindset shift mindset shifts you help people go through or anything like that? [00:16:11] Jonathan what is the first two steps to getting from that rejection to redirection path? [00:17:20] When when you go to a LinkedIn profile, what's the immediate thing you go to? Let's start with that, Jerry, and then go to John. [00:19:12] When it comes to the headlines, what is a common mistake you see people make repeatedly when it comes to their headlines? [00:22:02] What are some do's and don'ts that you can share? [00:23:32] What if we just don't feel like we're an expert enough to post content? [00:25:01] There's the creating content, but then there's the consumption of content. How do you how do you ensure that you're consuming good stuff? [00:26:12] There are a lot of good content out there as well, right? Once you have the good content filter down to get your feed full of stuff that you actually do want to see, then it becomes, Oh my God, there's so much good stuff and so many good tips, like, how the fuck do I apply this to my life? What am I supposed to do? Do you have like the tips or a framework on, on how you go about doing that. [00:26:34] In terms of making use of all the wonderful tips that people are sharing because sometimes they just get so many tips, they might just get paralyzed like, oh my God, what do I do? What are your tips on that? [00:31:31] Let's say you applied for a job. You're in the in the interview and you're showing up to an interview and you don't have much experience. Let's say it's an entry level job. So I just want to get your hot take on entry level jobs requiring experience. What are your thoughts around that? How can we break that need experience to get experience a cycle? [00:34:27] Should we worry about looking a job hopper in 2022? What are your thoughts on that? [00:36:52] Before we get to that phase again, job offers and all that stuff, we can't job help them see a job offers. How about those negotiations? That's the critical piece, I think, of the job process. Do you feel that people tend to be afraid to negotiate? And where do you think that fear stems from? [00:38:44] How do you ask better questions during an interview to get to know more about the culture and environment? [00:42:28] Is there a right or wrong way to answer to the "tell me about yourself" question. Jonathan, what do you think? [00:43:25] How should we answer the "what's your biggest weakness" question? Should we actually just say weakness or what's your tips there? [00:44:57] Talk about being an influencer, LinkedIn influencer, kind of the perils of being a LinkedIn influencers. What responsibility do you think it is? I don't know if I'm counted, I only got like 43,000 followers for whatever I'm influencer or not. But I feel like I have some responsibility towards people who consume my content. What are your views on that? What responsibility do we do we have towards towards those who are following us? [00:46:59] Have you guys ever gone to any types of bouts of kind of creative burnout? What was that like? How did you overcome it? What were some early warning signs that you're starting to get burnt out? [00:49:45] What's the right way to ask for a mentor? How do we identify who we want as a mentor? [00:50:59] How do you go about finding this person might be a good candidate or that that vetting process or what have you? [00:52:40] It is 100 years in the future. What do you want to be remembered for? Random Round [00:54:08] What song do you have on repeat? [00:54:41] What talent would you like to show off in a talent show? [00:54:59] What fictional place would you most like to go? [00:55:18] If you lost all of your possessions but one, what would you want it to be? -- Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://www.youtube.com/watch?v=DAkvvP6-TuQ&t=14s Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Find Jeremy online: https://www.linkedin.com/in/rjeremyadamson Watch the video of this episode: https://www.youtube.com/watch?v=UglmEt_CRQE Memorable Quotes from the episode: [00:31:19] "Design thinking is a great ideation framework for understanding based on the business outcome, how we can tackle that. It's five simple steps. The first one is to empathize with the stakeholder, and that's a word that I think we need to be saying a lot more in this practice is empathy." Highlights of the show: [00:01:22] Guest Introduction [00:03:04] Talk to us a little bit about how you got interested in data science and what was your path into the field like? [00:05:08] How much more hype has data science, A.I. and all that become since you first broke into the field? [00:06:26] What do you see happening in 2022 in data science and analytics? What's the big thing that you're excited or hopeful about? [00:13:34] What are some guiding principles that we should keep in mind to ensure that we're successfully building and leading those? [00:15:07] What's the etiquette behind the kicking of the doors? [00:16:48] We will get into 'design thinking' part of the book, but I want to double down on the 'process' aspect of the book. What is 'process' anyways and what is it all about? [00:18:16] What are some some ways that we can ensure that our processes remain parsimonious? And if you got any examples that you want to share with us. [00:19:50] Talk to us about comprehensive group of processes that that are required for for project success. [00:23:48] Walk us through prioritization projects. [00:25:25] Identifying things that are important, we talk about this with respect to a project scoping and planning that there's some questions that we should ask ourselves and ask our stakeholders. Two crucial ones. Can you share those questions with us? And what is it that we hope to get from from asking those questions? [00:27:47] When it comes to dealing with stakeholders or let's say we've identified that this is a problem that we should be working on, but how do we make it? How do we frame it from the business problem to an analytics problem? What are some questions we should use to tease out what we need to, to properly frame it? [00:31:06] There's something that you talk about called 'design thinking'. What is design thinking? What's it all about? And what does this have to do with 'process'? What does this have to do with data science? [00:32:42] It seems like designing requires a skills that are underdeveloped in a lot of data science and analytic professionals. How do we cultivate those skills and make that process enjoyable for everyone who's involved? [00:34:46] When it comes to executing a project, does Agile have a place in the data science world? [00:35:32] Do you have a structured approach for generating demand within an organization, especially for new teams where all business functions are our customers? [00:37:00] What is a SKU morph and how can we use this to our advantage in data science? [00:39:20] Are there, if you know of any studies about how agile methods can be applied to teams in data analytics or finance. [00:42:53] How can we start viewing ourselves as craftspeople? What do you mean by a 'bi craftsperson'? How can we start being ourselves as that? [00:45:34] It's been extremely hard to hire and keep great data scientists. Do you have any tips that have worked for you? You've touched on a few of those, but have you got any additional tips for that? [00:47:20] Apart from the technical skills, what is it that you look for in data science candidates? [00:48:39] How can an individual contributor embody the characteristics of a good leader without necessarily having that title? [00:50:11] It's 100 years in the future. What do you want to be remembered for? Random Round: [00:50:45] Let's just think about some interesting use cases for data science and machine learning in the aviation industries. What are a couple of ways that machine learning is being used there? [00:52:37] If you were to write a fiction novel, what would it be about and what would you title it? [00:53:00] What are you currently reading? [00:53:14] What are you currently most excited about or currently exploring? [00:53:51] What's something you learned in the last week? [00:54:02] What have you created that you're most proud of? [00:54:15] Have you ever saved someone's life? [00:54:21] What's the best compliment you've ever received? Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://www.youtube.com/watch?v=qHjKd4van4o Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Find Nick online: https://www.nicksingh.com/ Watch the video of this episode: https://youtu.be/7fzOYBkTHDM Memorable Quotes from the show: [00:12:47] "The part of math that I was interested in wasn't that crazy, crazy theoretical math. It was just like, Oh, how can we use data to drive better decisions? Like how can simple statistics and computing metrics and just keeping track of shit using numbers? How can that help build better products or build better systems? And that's what I learned in systems engineering. Combine that with some of my CS classes, which got me into a little bit more machine learning, and then it started clicking in my head of like, Oh, this data thing is really cool." Hightlights of the show: [00:00:40] Guest Introduction [00:03:26] Talk to us a little bit about where you grew up and what it was like there. [00:07:57] What is it about us (of Indian heritage) and software and data science? [00:09:11] Was there something you were always good at? Did you think you were ever going to be an author? [00:11:03] Was data science something that you were exposed to when you're young? [00:13:57] What is the business side of data? Please paint that picture for us. [00:19:22] Is it better to have blank space on a resume than neutral information? [00:23:34] LTalk to us about what this philosophy is for projects. [00:31:57] How do we demonstrate business value with a project, especially if we don't have on the job experience and are doing a project to demonstrate our technical ability? [00:39:20] You talk about cold emailing in your book. Is that just when someone messages somebody highly ranked on LinkedIn and leave it at that? [00:40:50] Let's say somebody sees this awesome job on LinkedIn and then started looking for people in that company. Should they go and message an individual contributor, data scientist and have them look at their profile or send a message to the CEO? Like who on the spectrum do they reach out to? [00:46:03] It is noticed that a lot of people that are new to the industry are new data scientists who are all up in their head thinking oh, man, like math and everything, thinking all about algorithms and their sleep. They think that these behavioral interview questions are just fluffy bullshit. Why do you think folks have this misconception? [00:50:10] You talk about a framework in the book at a high level. Can you share a bit of that framework for how you would answer that question (where the star format doesn't apply)? [00:52:34] Would you rather mention your knity gritty experiences from the past in an interview or do mention a little of a role that you played in math or astrophysics. Say that you're trying to get into a machine learning engineer role, can you share your response to that question with us here? [00:55:12] Auditing the "tell me about yourself" question. [01:04:50] What does product sense mean? What is it? Why are people afraid of it? Why does it seem like such a difficult skill? [01:11:35] What's the number one product sense question that you see being asked? [01:14:36] It is it's 100 years in the future. What do you want to be remembered for? Random Round [01:16:18] What do most people think? Within the first few seconds of meeting you for the first time. [01:16:47] You have this awesome blog post about books that you always bring up in conversations. One of them is written by probably my absolute favorite authors and one of my favorite books. That's Antifragile by Nassim Taleb. Talk to us about the three main takeaways you've gotten from that book. [01:21:19] What are you currently reading? [01:24:23] First question what makes you cry? [01:24:41] If you were a vegetable, what vegetable would you be? [01:24:50] What have you created that you're most proud of? [01:25:33] What's the best piece of advice you have ever received? [01:26:54] If you lost all of your possessions but one, what would you want it to be? [01:27:29] Do you ever sing When You're Alone? [01:27:52] What's your favorite candy? Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://www.youtube.com/watch?v=eYfHD1CkvRI Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Find David online: https://twitter.com/d_spiegel Read David's article "Will I live longer than my cat?": https://www.bbc.co.uk/news/magazine-19467491 Watch the video of this episode: https://youtu.be/pCWH97vBFmU Memorable Quotes from the show: [00:23:36] "...essentially what probability theory allows us to do is to make assumptions about how the world works, how the data is generated, and turn it and flip it around after we observe some data into statements about our uncertainty about underlying features of the world. We can do that, which of course is very explicit based on work indeed, where after processing data or uncertainty and it turns into uncertainty about the underlying quantities." Hightlights of the show: [00:01:29] Guest Introduction [00:03:08] Talk to us about how you first got interested in statistics and what was it that drew you to this field? [00:04:55] Why is it that it seems like mathematicians tend to dislike teaching statistics? [00:08:27] What is statistical science and what is it all about? [00:09:46] You talk about in your book, The Art of Statistics, how to handle problems and approach problems in statistics. You call the P, p, b, a C cycle. Tell us about that framework. [00:15:03] You mentioned in the book that statistics is to blame for the reproducibility and replication crises in science. Why? Why is that? [00:18:23] When we talk about induction and inductive inference, should the philosopher in us get worried at all about the problem of induction in statistics? [00:19:40] Tell our audience about the 'normal distribution'. [00:20:34] Do you have any examples of when inductive inference has failed in statistics that you could share with us? [00:22:15] Why do we need probability theory when we're doing statistics? [00:26:25] I think pouring into the Bayesian stuff is kind of taking a step back here, maybe first principles. But what is probability? How do we measure it? It seems like such a strange epistemological concept. [00:28:27] Can we say there's a at least some type of difference between epistemic probability and some physical or I believe you say aleatory? [00:30:03] Would there be a difference in the way that a philosopher or a statistician would interpret probability? [00:38:32] What's the Bayesian approach all about and why is it that courts in the UK are banning it or have banned it? [00:40:16] How is this (Bayesian approach) different from the frequentist approach to viewing probability? What's the central difference? [00:44:55] It seems like the prior distribution is something that makes base them so controversial. Why is that? [00:46:18] It seems like Bayes Theorem is the scientifically correct way to change your mind when you get new evidence, right? [00:48:18] David Deutsch mentioned lately about the Bayesian-ism, and he's having some qualms with Bayesian ism. He says that Bayesian-ism becomes controversial when you try to use it as a way to generate new ideas or judge one explanation against another. How do we reconcile that when we're faced with some epistemic. [00:49:51] About using it to help us in our everyday lives to make better decisions. How can we use Bayes in that context? [00:53:15] It is 100 years in the future. What do you want to be remembered for? Random Round [00:54:17] What do you believe that other people think is crazy? [00:55:02] What are you most curious about right now? [00:55:55] What are you currently reading? [00:58:33] What do you like most about your family? [00:58:53] What was your best birthday? Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://www.youtube.com/watch?v=I6uLiz4lTrU&ab_channel=HarpreetSahota%7CTheArtistsofDataScience Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://youtu.be/x26n7HmSYjw Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://www.youtube.com/watch?v=SYiQ1ncCGv8&ab_channel=HarpreetSahota%7CTheArtistsofDataScience Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Find Marcus online: https://twitter.com/MarcusduSautoy Watch the video of this episode: https://youtu.be/efIBVILq6WI Memorable Quotes from the show: [00:34:25] "...one has to learn the power of the short cut in statistics, which, you know, I tell the story about the we had this advert when I was a kid which which stated eight out of ten cats prefer a particular type of cat food. And, and we had a cat and I never remember anybody asking our cat what cat food it likes. So it was very striking that when I got to university, I learned about the power of sampling and the fact that, you know, to be able to there are 7 million cats here in the UK. How many cats would you have to ask to be confident enough to make that statement about?" Highlights of the show: [00:00:40] Guest Introduction [00:03:08] Talk to us about where you grew up and what it was like there. [00:08:15] Math is kind of just the language we use to describe it. What are your thoughts? [00:10:49] From your viewpoint, do you think math is an art? Is it a science? Is it a combination of art and science. How do you how do you view this? [00:13:52] What was it about Gauss when we talk about Mathametics? [00:19:02] Is there any virtue in human laziness? [00:21:52] Aristotle, idleness and noble leisure. Discuss. [00:21:59] Speaking of creativity and putting you out of a job, can you discuss a little more about what you talk about in your book about it? [00:27:18] Speaking of creativity, you took time in this pandemic to write a play. How is that coming along? [00:29:44] Fringe Festival in Winnipeg and London Fringe in London. [00:30:07] You shared a story in the book about how we can use math to fight off of vampires. If you could recount that story. [00:33:47] What are some dangers of using statistical shortcuts that we should be on high alert for? [00:39:34] "...data science can be dangerous if it's not combined with a deep understanding of where the data comes from." [00:40:33] Why is it that our that our brains aren't very good at assessing probabilities? 00:44:14] Why is it that some people find that shortcut that Reverend Bayes discovered so controversial? [00:47:02] You talked about the philosophical view of probability. Is it frequentist approach, the Bayesian approach? How do you view probability? What's your take on that? [00:49:41] What is the Lovelace test and in what ways is it different from the Turing test? [00:56:25] You talk about a few different types of creativity in your book, please eloborate. [01:06:17] What is it about a mathematician's mindset that is deterministic and foolproof and of engineers? [01:09:34] It is 100 years in the future. What do you want to be remembered for? Random Round [01:10:46] What was your best birthday and how old were you at that birthday? [01:11:42] What's the worst movie you've ever seen? [01:12:06] What would you do on a free afternoon in the middle of the week? Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://www.youtube.com/watch?v=30uugRuW5E&abchannel=HarpreetSahota%7CTheArtistsofDataScience Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Find Danny online: https://www.datawithdanny.com/ Watch the video of this episode: https://youtu.be/VgQ_Hhq4AlM Memorable Quotes from the show: [00:34:25] "I think in general, just we should really be out there to help others instead of trying to help ourselves in a way. Like I know of a few larger names who the social media presence is, their business, essentially. And I know that's really important. Like everyone has to make money, feed their families, buy all the things that they need in life and all that aspirational sort of things. But in a sense, like for me, like I don't know if this is this might be similar for you as well." Hightlights of the show: [00:00:40] Guest Introduction [00:02:32] Where you grew up and what it was like there. [00:03:57] What's life in Sydney been like for you? Have you come to North America? Have you done a compare and contrast that what's different and what's the same? [00:06:20] What kind of kid were you during high school and what did you think your future would look like? [00:10:35] You and I somehow came from a similar type of background, having a kind of walk that actuarial path we're entering into this data science kind of field. Tell us what was your experience like with those exams. [00:12:52] What was it about kind of doing that actuarial work that made you want to leave it behind and move to this data thing? [00:18:13] How did you figure out that what it was that you needed to figure out in order to make it in this field? [00:22:43] How do you try to ensure that you've got as fresh a perspective as possible? Do you even need a fresh perspective as possible? What are your thoughts on that? [00:29:14] We're just talking about what it means to be a data science influencer. What are your thoughts on what it means to be a a data science influencer? [00:32:57] Do we have an influencer quality - What responsibility do we have to these people that are following us? [00:36:51] What do you consider the difference to be between coaching and mentorship? [00:39:27] How can somebody go and go about finding a mentor? [00:43:07] What elements can you take and apply to this new thing that you want to do in the essence of creativity as well as finding different things that on the surface of it don't look like they belong together. But when you put them together, it actually gels quite nicely. [00:44:40] Do you have any tips on on how I can be a better mentor? [00:53:09] Talk to us abouth the love of SQL. How did this happen? Is this something that you've always just enjoyed? Has SQL always been your favorite part of the entire data science ecosystem? How this deep, deep love of SQL happened? [00:57:23] Can we draw the line between a data analyst and a data scientist? [01:08:32] What's your take on the importance of taking action on an idea you have in your mind there? [01:12:00] It is 100 years in the future, what do you want to be remembered for? [01:13:01] At what point did your meme game get so dank? [01:15:21] What are you currently reading? [01:17:05] What song do you currently have on repeat or stuck in your head? Random Round [01:18:00] Who inspires you to be better? [01:18:09] What's the best piece of advice you've ever received? [01:18:15] Who is one of your best friends? [01:18:29] If you were a vegetable, what vegetable would you be? Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://youtu.be/LR81rcjuaFk Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Find Chanin online: https://th.linkedin.com/in/chanin-nantasenamat Watch the video of this episode: https://youtu.be/pCHubISFBTI Memorable Quotes from the show: [00:31:42] "So I would believe that scientific method would be the science part of data science, and the data could be biology, chemistry, physics, business data, economic ecology. So I would believe that it's pretty much like a plug and play like data could come from many discipline. And then the analytic part, the machine learning part would be to take that data and make it into an interpretable model." Highlights of the show: [00:00:36] Guest Introduction [00:03:12] Where you grew up and what it was like there? [00:04:22] What brought you back to Thailand? [00:05:15] How different is your life now than what you thought it would be growing up? [00:07:03] When it comes to making YouTube videos, what is your most favorite part about making the YouTube videos and what is the part that you just liked the least? [00:08:02] What part of it is the toughest? Is it just that the editing and the blogging and stuff like that? Or is there some parts of it where you're just like, Oh, man, I hate doing this? [00:09:47] What is bioinformatics and how did you get into that? [00:11:22] Was there any additional upskilling that you had to do in machine learning or data science topics? And if there was any additional upskilling, what was your process to acquire that knowledge? [00:17:19] "How do I figure out what projectsI want to do, how to figure out what I want to research?" hat advice do you typically give to such questions? [00:19:00] What is drug discovery? Where does data science enter into the mix here? [00:22:28] Do you have any interesting use cases or studies you can share with us that talk about the involvement of machine learning and drug discovery, like a friendly, easy to read paper or maybe one of your YouTube videos if you got something like that? [00:26:26] Do you know of anything that's been released on the market that has used this (drug discovery) approach? Is it widely used? Is it commonly used? Or is this kind of something that's right now just a theoretical idea? [00:27:09] YouTubing, but where did that spark to help other data scientists come from? [00:31:40] where is the science in data science? [00:34:30] The methodology, a traditional machine learning problem or deep learning one. The process methodology is a little bit different. You worked with both of those, how would you say it's compare and contrast that if you would for us? [00:36:50] Talk to us about a few of your blog posts. [00:43:43] It is 100 years in the future, what do you want to be remembered for? [00:44:45] When it comes to the future of of data science and machine learning, what applications are you most excited about in the field of drug discovery or bioinformatics? What gets you hyped up when you think about it? [00:46:38] What are you currently reading? [00:48:06] What song do you currently have on repeat? [00:48:38] What are your pet peeves? [00:49:02] Do you have any nicknames? [00:49:22] What talent would you show off in a talent show? [00:49:44] When was the last time you changed your opinion about something major? [00:51:29] What's your favorite city? Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://www.youtube.com/watch?v=32znIxJoFRo Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Find Christina online: https://www.linkedin.com/in/christinastathopoulos Watch the video of this episode: https://youtu.be/FCQZfuhV6vY Highlights of the Show: [00:01:32] Guest Introduction [00:03:24] Where did you grow up and what was it like there? [00:04:18] You spent a decade abroad in Spain. How did that happen? [00:06:28] How did you transition into analytics? [00:08:31] How did you learn another language as an adult? Was that challenging? How did you figure that out? [00:13:48] You and Kate are quite busy. How do you balance all of these activities, all of these speaking engagements and teaching, plus having a full time job? [00:18:17] How did you develop this reading habit and how are you getting all these books? Are you getting them delivered to you or do you have a book exchange thing? How's this working? [00:20:35] Do you do audiobooks or just strictly so? [00:21:50] How can someone who's new to this space (analytics) decide which direction is right for them? And how did you figure out what direction you wanted to go into? [00:24:53] What are some soft skills that you think have helped you really excel in your career? [00:29:16] Russell defined your multilingual skills with spoken and written language. Do you find that they help you when translating between different coding languages? [00:31:08] How can we simplify complex tasks? [00:32:59] When you put yourself into their shoes, is there some kind of universal thing that most CEOs tend to care about or universal points that you've noticed through all these interactions that you've had, if such a thing could exist? [00:38:18] How did you overcome technological challenges? If you face that challenge at all. What I'm trying to ask is learning new things as they come up in your career. How do you handle that? How do you manage that? [00:42:51] Is there anything that you feel like you're just a natural at? [00:43:31] In terms of the new methodologies and new technology that is coming out, is it mostly the academic research stuff? Is the cutting edge deep learning stuff? What do you find more fascinating? [00:46:20] "How do you practice being present during tough times and tie back to your purpose with the work you do?" [00:49:39] If you had any words of advice or encouragement for the women who are breaking into or that are currently in our world of data science? [00:52:43] What can we do to foster inclusion of women in data science? [00:57:04] It is 100 years in the future. What do you want to be remembered for? Random Round [00:57:54] You've done a lot of traveling 50 countries. What's the most beautiful place you've ever seen? [01:02:39] What song do you have on repeat? [01:05:19] What incredibly strong opinion do you have that is completely unimportant in the grand scheme of things? [01:06:01] What was your best birthday? [01:06:10] Do you have any nicknames? [01:06:24] What's your worst habit? Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://youtu.be/6wNvlO8Jj7o Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Find Natalie online: https://www.figure8thinking.com/about/ Watch the video of this episode: https://youtu.be/3Dr7OcyQj1M Highlights of the show: [00:01:32] Guest Introduction [00:03:34] Where did you grow up and what was it like there? [00:08:04] Talk to us about the idea of “indoctrination to education”. [00:12:35] Your interesting ‘creativity research’, when did that start? How did your interest in that get sparked? [00:18:24] How can we make creativity more accessible and not just something that feels like it's in the domain of artsy people? [00:23:15] What is your definition of creativity? [00:27:27] Discuss the aspect of wonder and rigour. [00:29:09] What's wrong with the way that we're currently asking questions? [00:38:17] Walk us through what design thinking is and how does that help us be more creative? [00:40:58] What is divergent and convergent thinking? [00:50:47] Talk to us about the remix, the reframe and repurpose. How they help play a role in being creative? [00:53:04] Talk to us about 'Fashion thinking'. [00:56:20] It is 100 years in the future. What could it be remembered for? Random Round [00:57:13] What are you currently reading? [00:57:37] What song do you currently have on repeat? [00:58:22] What's the best thing you got from one of your parents? [00:58:31] In your group of friends, what role do you play? [00:58:41] What fictional place would you most like to go to? [00:59:02] Pizza or tacos? Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://youtu.be/7l-pB7RkCJA Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Find Andrew online: https://www.linkedin.com/in/andrew-jones-data-science-infinity Watch the video of this episode: https://youtu.be/hiEEAIGP8Zo Memorable Quotes from the Show: [00:20:55] “You need somebody in there to be putting the nuance on that to make it actually work. I think for me as well, like Auto, where ML doesn't have any business sense necessarily, so it doesn't know what problems to solve or it doesn't know why it should solve them. So I think humans are still a huge part of that. I don't think that's going away anywhere soon. It's just an evolution and data scientists are going to start, you know, there's going to be bits where automation comes in and helps us do our jobs even better. But I don't think it's going to take away jobs necessarily. I don't have any particular fear about that.” Highlights of the Show: [00:01:18] Guest Introduction [00:03:20] Where did you grow up and what was it like there? [00:06:19] When you were in high school, what did you think your future would look like? [00:07:12] At six foot seven. It's a shame that you did not get into basketball. Is that right? [00:07:48] Did you start doing analytics in New Zealand or start in London? Walk us through that journey. [00:10:39] What's the toughest part about transitioning from SAS into python? [00:16:25] You've been in this field for over a decade. How far has it come since you first broke into it? [00:19:13] Can you share a hot take with us on where you think the field of data science is headed? [00:33:29] Talk about your mission to help develop data scientists. [00:39:28] What makes an employable data scientist different from an unemployable one? [00:42:07] Where do you think most data scientists go wrong in terms of their own career development? [00:45:07] “How to choose the right model to train the data?” [00:49:06 Is there a field within machine learning that focuses on incorporating human concerns through technology development? [00:51:58] “What advice do you give social scientists that are learning data analytics? Any particular hints for psychologists trying to understand acceptable norms of behavior when creating data science projects?” [00:54:04] Talks to us about the top five reasons that candidates get rejected. [00:58:13] When it comes to career growth and development. What's the biggest lesson you learned the hard way that you want to make sure no one else makes? [00:59:49] It's 100 years in the future. What do you want to be remembered? Random Round [01:01:18] What do you think will be the first video to hit 1 trillion views on YouTube? And what will that video be about? [01:03:29] What are you currently reading? [01:05:09] What song do you currently have on repeat? [01:06:30 If you had to change your name, what would you change it to? [01:07:26] What's on your bucket list this year? [01:08:40] What's the story behind one of your scars? [01:09:51] What languages do you speak? Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://youtu.be/2kCDJbiTCk8 Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Read Brittany' book: Bigger Than Leadership https://www.amazon.com/Bigger-Than-Leadership-Influence-Inspiration-ebook/dp/B093PJGB6R Watch the video of this episode: https://youtu.be/HP-_FJh8UGY Memorable Quotes from the episode: [00:33:19] “No matter who you are, no matter where you are, you do leave a visible,or like a physical, but also a more mental footprint everywhere you go. That is something that's really powerful.” Highlights of the Show: [00:01:18] Guest Introduction [00:02:34] Where did you grow up and what was it like there? [00:04:05] When you were in high school, what did you think your future would look like? [00:07:44] Talk to us about your personal definition of what leadership is, what it means to you, and then why write about leadership? [00:10:30] Who is your book for? [00:12:36] Do you think a lot of people tend to feel that way, like they don't see themselves as leaders or they don't realize that they have this leadership ability. Would you agree with that? Why? Why not? [00:14:35] What was the process like while writing your book? How did you manage your knowledge? How did you manage the notes? And then finally, how did all that come together in a book? [00:16:51] Talk to us about the importance of stories and why they serve as such useful reminders for us. [00:19:29] How do you balance all the activities - full time course load, writing a book in the middle of a pandemic? How did you manage all that? [00:22:55] “Can you tell us more about the role of introspection in your writing work and the role of introspection in stories of leadership?” [00:25:55] Do you have an introspection practice that you undertake? Is it just sitting and thinking, is it sitting in journaling? Is it going for a walk and thinking? How do you get your introspection on? [00:28:58] How were you able to keep a narrow focus while exploring so much data in your writing? [00:32:41] Talk to us about the “Three Eyes framework”. You touched a little bit on the intentionality aspect of it, but talk to us about how these three, I guess what these three eyes are and how they relate to leadership. [00:43:02] Talk about the difference between leadership and mentorship. [00:45:36] Can you share some tips with the audience for how we can go about finding a mentor for ourselves? [00:49:17] What tips would you have for someone who finds themselves in a position similar to mine where all of a sudden people have started following them on LinkedIn and or other social media and have started to view them as mentors. What advice would you share? [00:54:20] It is 100 years in the future. What do you want to be remembered for? Random Round [00:56:30] When do you think the first video to hit 1 trillion views on YouTube will happen? And what do you think that video will be about? [00:57:11] What do most people think within the first few seconds of meeting you for the first time? [00:58:48] Talk to us about what the book title “Bigger Than Leadership” means to you. [01:00:53] What are you currently reading? [01:02:12] What is your procedure for taking notes? [01:03:11] What song do you currently have on repeat? [01:04:22-01:04:28] When people come to you for help, what do they usually want help with? [01:05:45] What is your theme song? [01:06:26] What issue will you always speak your mind about? [01:07:25] Who inspires you to be better? Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://youtu.be/tzg4SkNo4g0 Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Find Joe online: https://www.linkedin.com/in/josephreis Joe is a business-minded data nerd who’s worked in the data industry for 20 years. In his two decades as a practitioner he’s worked on the full gamut of data tasks from statistical modeling, forecasting, machine learning, data engineering, data architecture, and almost everything else in between. He’s taken all that experience and started his own venture and is currently the CEO of Ternary data. Watch the video of this episode: https://youtu.be/6jGmXBaTJkI Memorable Quotes from the episode: [00:42:09] "...My other piece of advice, which is, do you lose money for the firm? I'll be understanding. If you lose a shred of reputation, I will be ruthless. Let's talk with me. Right. Reputation is everything. As he also says, it takes a lifetime to build a reputation. It takes 15 minutes to destroy it. So when we started our business, I thought it was interesting. We didn't really care about the money. We cared about reputation and cared about doing great work, meeting great people and just, I think developing good relationships. I always optimizing for reputation. I think we thought if we could build that pile of reputational capital, the money would follow. The reverse is rarely true, though. In the short term, you can build as much money as you can, but you can destroy your reputation. And then who's going to want to do business with you?" Highlights of the show: [00:01:11] Guest Introduction [00:03:34] Joe, where did you grow up and what was it like there? [00:05:22] What were you like as a high school kid? What did you think your future would look like? [00:06:46] When you'd make the move over to Salt Lake City? Was that when you started working? Did you go to school there? [00:09:08] What was it like kind of when you first started out and what drew you to this kind of field (data science)? [00:14:02] Where is the science in data science? Is there any science in data science? Is it scientism? [00:26:10] How did you guys link up and decide to start ternary data and can we even get the story behind the companies name as well? [00:27:23] What are some problems that you just see as a consultant pop up over and over? [00:34:06] Do engineers add value and how should we think about a return on investment for the work that they do? [00:41:23] Talk to us about your blog post about the concept of reputational capital. [00:43:04] Do you have any tips for people who are just early in their data science career. In their first job as a data scientist, how can they accrue some of this 'reputational capital'? [00:45:56] How reading science fiction has made you a better technologist? What science fiction has done for you, has it made you a better technologist? [00:47:44] What would you say is the one sci-fi work that's had the biggest influence on you as a technologist? [00:51:04-00:51:17] You've got such a dope setup here. What's all this about? The keyboards? You got turntables, you got multiple keyboards. Are you making your music. Do you got any undercover Spotify? [00:52:59] It's 100 years in the future. What do you want to be remembered for? Random Round [00:54:02] When do you think the first video to hit to 1 trillion views on YouTube will happen? When will that happen and what will that video be about? [00:55:33] What song do you have on repeat? [00:55:53] What are you currently reading? [00:59:19] What's kind of your process when you're reading? [01:03:12] What talent would you show off in a talent show? [01:03:39] What do you mean by organizational behaviour? Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://youtu.be/voMA7BvAHJ8 Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Find Brent online: https://www.linkedin.com/in/brentdykes Watch the video of this episode: https://youtu.be/QcihRq9ieWE Highlights of the show: [00:01:21] Guest Introduction [00:03:33] Talk to us a bit about where you grew up and what it was like there? [00:04:58] You're still involved in the technology field and still involved with 'Data' in a sense. So is life really different than what you imagined it might be? [00:08:36] ...the new indicating or talking or informing what is there,subtle differences is it glaring differences? Talk to us about that. [00:14:05] I love philosophy, and Aristotle is definitely one of my favorites. So I'm wondering what can Aristotle teach us about persuasion and storytelling? [00:15:18] "Telos" [00:20:55] System one and System twos. [00:21:00] If most of our decisions are very emotional, then how is it that we can make better decisions in spite of this emotional nature that we have? [00:24:09 How do you define the term "motivated reasoning"? [00:27:25] What are the differences in the ways that facts and stories activate our brains? Are some other differences in the ways that you know, facts and stories that activate our brain? [00:31:48] What is a Data story like? Isn't it just the same as a dashboard with visuals or is it something else? [00:37:19] What are the elements of an insight? How do we go from fact to insight? [00:40:08] Is there a distinction between just the old fashioned insight and like an actionable insight? How do we distinguish the two? [00:47:15] What is the "FOUR D" framework? [00:52:32] We might have an audience member that's a key audience member, and they just want the facts. How do we how do we handle that situation? [00:59:03] What's the difference between a Data story and a Data forgery? [01:04:41] You talk about Cognitive Biases, Logical Fallacies in your book, what are these and why are they important to watch out for? Why should we keep an eye out for these things? [01:10:45-01] It is this it's one hundred years in the future what do you want to be remembered for? [01:12:23] What are you currently reading? [01:12:43] What song do you currently have on repeat? [01:13:26] If you lost all of your possessions, but one, what would you want it to be? [01:13:48] What's your worst habit? [01:13:55] What's your favourite, candy? [01:14:12 What's one of your favorite comfort foods? [01:14:24 What's something you learned in the last week? Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://youtu.be/lDh5crPq_Yc Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Find Fabrice online: https://twitter.com/fabricemesidor Watch the video of this episode: https://youtu.be/HfPZkuU65OY Memorable Quotes from the episode: [00:42:14] "I find that coding and math. I mean, the entire machine learning models today are really complex. So pick something to have fun with. You don't have to be stuck with quickly coding enough to start working on something that you don't like. So you need to take a project that you will have fun. You just enjoy. And the second thing is, don't be scared of the challenge." Highlights of the show: [00:01:17] Guest Introduction [00:02:57] Where you grew up and what it was like there? [00:05:05] You grew up in Haiti. In high school, what did you think your future would look like? Do you think you'd end up in the middle of winter in York? [00:07:19] Do you like microeconomics or macroeconomics better? Which one do you do you prefer? [00:08:55] How did you end up in Papua New Guinea? What was it like working in Papua New Guinea like? [00:16:48] Share some tips with us on how to remain focused. [00:18:42] Breaking into data science, you had to really upskill in Python. How did you apply those (excel skills) techniques when you're learning Python? [00:20:48] Share some tips for public speaking and giving talks about Data science? [00:30:00] Talk to us about your project idea. How did you get the idea for this project and what was what was your big takeaway from it? [00:31:54] How'd you get the Data for the movie scripts? [00:33:23] Applying machine learning to hip hop lyrics, so I thought that was really cool. So walk us through how you came up with the idea for this project. [00:34:59] While applying machine learning to hip hop lyrics. what was your problem statement? What methodology did you use? Did you did you grab just the lyrics or did you grab the audio? Or did you combine audio and lyrics? How did you piece that project together? What was the big question that you're trying to answer? [00:37:48] Did you have any type of criteria for which songs to include and which song not to include? [00:42:11] What can the audience take away from this so they can go create some creative stuff for themselves? [00:43:55] Do you have some favorite places that you go, some websites or anything like that? [00:46:45] How do you guys use data science to to to help people like meet their goals? [00:48:42] It is one hundred years in the future. What do you want to be remembered for that? Random Round [00:49:35] If you were to write a fiction novel, what would it be about and what would you title it? [00:50:21] When do you think the first video to hit one trillion views on YouTube will happen and what will it be about? [00:51:49] What are you currently reading? [00:52:29] What song do you have on repeat? [00:53:47] What are you interested in that most people haven't heard of? [00:54:42] How long were you able to hold your breath for? [00:55:23] What would you do on a free afternoon in the middle of the week? [00:55:32] What's the best thing you got from one of your parents? [00:56:45] Pancakes or waffles? Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://youtu.be/h2JVRSR22Ec Resources: https://conference.measureofmusic.com/ Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Find Justin online: https://www.linkedin.com/in/justingcgu Watch the video of this episode: https://youtu.be/78sZh6iwoj0 Show Highlights: [00:01:00] Guest Introduction [00:01:44] Where you grew up and what was it like? [00:04:41] It (was) assumed that there are only three possible career choices. Either you can be your doctor, an engineer, or it could be a failure. Was that the same kind of mentality that you had growing up with your parents? [00:13:22] I'm guessing that person didn't grow up in the internet era to be able to come with these really interesting ideas that you have. What's your thoughts on that? How did you come up with some great ideas that you've discussed. [00:17:14] Why is career services not the core piece of the college offering? [00:33:00] Do you think there are some myths out there associated with the ATS applicant tracking system? [00:43:05] Share some tips on how to make a good LinkedIn headline. Do you have any tips you can share with us for that? [00:48:05] What cheat code can you share with us with respect to the 'About Me' section? [00:52:48] it's one hundred years in the future. What do you want to be remembered for? [00:54:36] What are you most inspired by right now? [00:55:32] What do you believe that other people think is crazy? [00:58:00] What song do you currently have on repeat? [00:58:32] Which fictional place would you most like to go to? [00:59:28] What is your theme song? [01:00:14] Do you got any nicknames? [01:01:03] Who is one of your best friends and what do you love about them? Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Happy Hour 69 hosted by Antonio Ivanovski Watch the video of this episode: https://youtu.be/c1Pd6hK4NoE Resources: https://coolhunting.com/style/puma-satori-lux/ https://onthemarkdata.medium.com/making-sense-of-ethereum-data-for-analytics-17655c4859d0 https://www.instagram.com/lizandmollie/?hl=en https://www.sound.xyz/soulection/untitled-001 Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://youtu.be/yXCUm7au25U Memorable Quotes from the episode: [00:23:18] "Positivity paradox is that when you feel like you have to be positive, you feel worse because you're required to do what's called surface acting, and that's also I think it's very similar to emotional labor. This shows up a lot in customer service jobs. So if a customer is being really rude to you and you kind of put a smile on your face, pretend like they're being totally reasonable and take whatever vitriol they're spitting at you." Highlights of the Show: [00:00:46] Guest Introduction [00:03:16] Talk to us about where you grew up and what it was like there? [00:07:34] What did you think your future would look like when you grew up? [00:12:37] Talk to us about distinction between emotional intelligence and being reasonably emotional. What's the difference between these two kind of ideas? [00:17:40] How do you find space throughout the day to kind of just detach from some of these demands that you have of your time? [00:23:10] Talk to us about the positivity paradox. [00:29:07] Can you share some tips for newbies who are coming into an organization where maybe there's already these in-person relationships that have been developed and you're joining a team of colleagues kind of in this remote sense as a person on a screen like how can we develop meaningful work relationships if we're coming into a new environment in this virtual kind of world? [00:32:11] Talk to us about the user manuals and how can they help with developing and building team cohesion? [00:33:59] I really like that idea of the user manual but is this something that we can implement regardless of, you know, the depth or length of a work relationship? [00:37:06] How can we start doing some implementing some of the stuff that we're learning books like yours? [00:46:31] What are some other tips you might be able to share with that with our audience that find themselves in that situation where they've teammates now? [00:51:07] How do we go about defining or cultivating a team culture? [00:56:47] What about those people who just always seem to disagree and question everything that comes out of our mouth, right? How do we deal with with these people? [01:00:37] How we can use our voices to support the women in Data science and just women in our organizations in general? [01:04:40] Random round. [01:04:41] It is one hundred years in the future. What do you want to be remembered for? [01:07:16] When do you think the first video to hit one billion views on YouTube will happen? [01:08:35] What are you currently reading? [01:09:22] How do you effectively tell an accurate story about Data to an audience that might not be Data savvy? [01:09:33] What song do you have on repeat? [01:10:00] What languages do you speak? [01:10:09] Who is one of your best friends and what do you love about them? [01:11:42] What's the best thing you got from one of your parents Legos? [01:12:43] What's your go to dance move? Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://youtu.be/Y1xrax0G86c Resources: https://intel.wd1.myworkdayjobs.com/External/job/US-Oregon-Hillsboro/Enterprise-Master-Data-Architect---Technical_JR0206661 Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Find Alyssa online: https://www.linkedin.com/in/sophiaalyssasimpson Watch the video of this episode: https://youtu.be/IqDE0kZOyag Memorable Quotes from the Episode: [00:24:42] "The best Data is is real data that is generated either by humans. Sometimes that's emails or whatever that use case is that you're solving. So I'll take a frequent use case, which is often like prioritization of support. Tickets is a classic model that teams want to build inside a lot of different types of organizations. You have zillions of support cases coming in for, and you want to just categorize them or you want to understand which ones are most severe that need to be answered first." Highlights of the Show: [00:01:27] Guest Intro [00:03:05] You mentioned being an unlikely A.I. leader in your book, please talk to us about that. [00:04:29] What could possibly go wrong if all we did was focus on creating accurate machine learning systems and just focus on that accuracy metric? [00:08:08] Can you share some strategies with us for identifying the types of problems that A.I should solve? [00:11:57] What is the Goldilocks problem? How do we define the Goldilocks problem? [00:13:21] Can you share some tips with us to understand or tell, at least if a problem is going to be well suited to using machine learning? [00:24:21] How do we make sure that it's the right data that we're using? [00:28:34] If we have data that needs annotation, how do we check the quality of those annotations? How do we know where to go to get annotated? Do you have any tips around that? [00:36:03] Talk to us about the importance of Data strategy. [00:38:59] How do you deal with challenges like data governance in an organization if you face those? [00:40:21] Being a woman in tech, if you might be able to just share some advice or words of encouragement for the women. [00:45:03] Random Round. [00:45:04] It is one hundred years in the future. What do you want to be remembered for? [00:45:40] When do you think the first video to hit 1 trillion views on YouTube will happen and what will that video be about? [00:46:38] In your opinion, what do most people think within the first few seconds of meeting you for the first time? [00:46:56] What are you currently reading? [00:47:34] What song do you have on repeat? [00:48:06] What's your worst habit? [00:48:30] What's your favorite candy? Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://youtu.be/DnPVmB3vAEM Resources: https://docs.python.org/3/library/pdb.html https://pythonexamples.org/python-breakpoint-example/ https://pythontutor.com/ https://www.bvp.com/atlas/roadmap-data-infrastructure Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://youtu.be/jsNZCiTGWVM Memorable Quotes from the show: [00:04:37] "...When you open the book, the first thing you see is not financial advice. I am not a CFA. I'm on a talent. I have no mechanism to understand your personal financial situation. My goal, which I say in the book, is to transfer my way of thinking to like a book so that you can understand how I think about this stuff in a sort of economics and finance so that you can make an intelligent decision of like what percent of my investment portfolio should they allocate to this crazy bitcoin nonsense." Highlights of the show: [00:00:49] Guest Introduction [00:01:40] How you got interested in blockchain in the first place? [00:05:17] Who did you write this book for? [00:06:33] You also talk about some 'stablecoin; What the heck does that even mean? [00:07:55] What causes the prices of coins go super high and skyrocketing? [00:10:23] When people talk about blockchain and crypto, can we conflate those two? When I say crypto, does that just mean a coin or does crypto also refer to blockchain? [00:13:13] Why do we have blockchain when we do have PayPal? [00:15:06] Talk to us about "Finan". [00:16:20] What is money and why should inflation affect how we think about money? [00:23:39] Ethereum. [00:36:25] What do 'liquidity' and 'correlation' mean and can you help us out with an example? [00:42:52] What 'loss aversion' is all about? Can you describe this concept? Is that why losing money hurts us because it takes so much more effort to get it back? [00:44:52] What's the average person want from finance and how can decentralized finance be useful for them? [00:50:15] Talk about some traits of a good portfolio? [00:55:06] Concept of how to pick a 'protocol'. What do you look at when you're picking a protocol? [01:05:06] It's one hundred years in the future. What do you want to be remembered for? [01:06:21] Talk about some of your interviewing experience(s). [01:18:43] What are you currently reading right now? [01:19:38] What is one of your favorite smells? [01:20:15] What's something you wish you figured out sooner? Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Support the show: https://www.buymeacoffee.com/datascienceharp Watch the video of this episode: https://youtu.be/Xeanz9yORZI Resources: https://en.wikipedia.org/wiki/5Dopticaldatastorage https://en.wikipedia.org/wiki/TheFeed(BritishTVseries) https://en.wikipedia.org/wiki/Upload(TV_series) https://qr.ae/pGB0pB https://studios.disneyresearch.com/category/robotics/ https://twitter.com/mxcl/status/608682016205344768?s=21 https://vinvashishta.substack.com/p/machine-learning-is-the-key-to-metaverse https://www.starwars.com/news/the-mandalorian-stagecraft-feature https://www.wired.com/story/notpetya-cyberattack-ukraine-russia-code-crashed-the-world/ https://www.youtube.com/c/SQLBI Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: Support the show: https://www.buymeacoffee.com/datascienceharp YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Watch the video of this episode: https://youtu.be/wvkxi-Et29M Find Loris Marini online: https://www.linkedin.com/in/lorismarini/ https://www.discoveringdata.com Support the show: https://www.buymeacoffee.com/datascienceharp Memorable Quotes from the show: [00:33:01] "We all matter, we are all part of this and we need one another. I can't do that a science well, if the data is not reliable, if it's not trusted, if it's not connected to the business via metadata by a data management program that touches anyone. And so it's really a mind, a change of of mindset from. You can add value as a team in isolation to, well, not really. Data is the common denominator to everything we do, whether we like it or not. Everything we do generates Data." Highlights of the Show: [00:01:27] Guest Introduction. [00:03:01] Where did you grow up and what was it like there? [00:05:13] What the heck is quantum photonics and how did you get into that? [00:08:51] How did you go from awesome, crazy physics stuff into Data science? [00:12:41] Talk to us about your experience of hardcore physics and research and how did that experience lead you into the Data project? [00:14:58] What did that look like when you were venturing out as the first data scientist? [00:17:57] Data architecture. Talk to us about that transition. What was that transition like? What made you be like, "Oh my God, I need to put the Data science down and pick up the Data architect stuff" [00:21:11] What is the difference between Data engineer and the data architect? [00:24:47] What do you think a data scientist at a minimum should know about Data architecture and the role that Data architect plays? [00:35:27] You're talking about the difference between data, information, knowledge and strategy. What's the difference between these? How does data, information or knowledge play into a strategy? [00:40:44-00:40:46] What's the name of that podcast by Brian O'Neill? [00:53:03] I love creating machine learning models and then you're trying to do stuff and then you realize that your hands are tied because there's no infrastructure in place; there's no desire or nobody cares about your fancy algorithms and anything like that. How can we start making a culture happen for success? [00:58:04] Talk about this latter of Data needs that goes from data integration, data access and data transformation kind of walk us through that process and then talk to us about why transformation that part is so hard. [01:02:03] It's one hundred years in the future. What do you want to be remembered for? [01:04:00] What do you think is the most mysterious aspect of the universe, which you say that this uncertainty principle is that? Or is there a different thing that is more mysterious than that to you? [01:05:02] When do you think the first video to hit one trillion views on YouTube will happen and what will that video be about? [01:05:33] Who do people tell you that you look like? [01:06:10] What are you currently reading? [01:07:17] What song do you currently have on repeat? [01:08:02] What's the last book you gave up on and stopped reading? [01:08:45] What fictional place would you most like to go to? [01:09:21] What languages do you speak? [01:09:25] If you were a vegetable, what vegetable would you be? Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Watch the video of this episode: https://youtu.be/NPIjuY_0HYU Support the show: https://www.buymeacoffee.com/datascienceharp Resources: http://ecai2020.eu/papers/348paper.pdf https://arxiv.org/pdf/1912.10564.pdf https://cds.nyu.edu/wp-content/uploads/2019/06/RDSTentativeSyllabus.pdf https://dagshub.com/ https://discord.gg/ngNdE5Tvzy https://diversity.google/annual-report/ https://hal.inria.fr/hal-01522418/document https://insights.stackoverflow.com/survey/2021#salary-comp-total https://www.kaggle.com/discussion https://www.linkedin.com/feed/update/urn:li:activity:6889576309601640448/ https://www.linkedin.com/in/reid-blackman-ph-d-0338a794/ https://www.microsoft.com/en-us/ai/responsible-ai-resources Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Watch the video of this episode: https://youtu.be/JN7Anqiv2fU Find Dr. Joe online: https://www.linkedin.com/in/jwperez Support the show: https://www.buymeacoffee.com/datascienceharp Memorable Quotes from the Episode: Highlights of the Show: Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Watch the video of this episode: https://youtu.be/nLf0_0I6uvU Resources: https://abseil.io/resources/sweatgoogle.2.pdf https://register.gotowebinar.com/register/6783119648565141771 https://services.google.com/fh/files/misc/practitionersguidetomlopswhitepaper.pdf https://theartistsofdatascience.fireside.fm/andy-hunt https://www.benjerry.co.uk/flavours/flavour-graveyard/rainforest-crunch Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Scott Taylor: https://www.linkedin.com/in/scottmztaylor/ https://www.metametaconsulting.com Watch the video of this episode: https://youtu.be/LZHB6wcAUdg Memorable Quotes from the Episode: [00:26:52] "... if the Data science community worked more closely with the Data management community, I think we can, you know, let's stamp out wrangling or at least munching. Let's stamp out munching at least in our lifetime, since so many of those issues that people spend time on could be solved in the Data management side of the house. They may even have that data. I don't know how many times I learned at DB even at DB, where people were just like kind of starting over looking at something, it's like, you know, there's an existing list somewhere." Highlights of the Show: [00:01:29] Guest Intro [00:03:42] Where'd you grow up? What was it like there? [00:05:07] How did you get education in the United Nations School? [00:07:06] How how did you get into Data? [00:07:54] What was the first job you had? [00:09:52] How did you end up learning about "Data"? [00:12:56] What are the four Cs you talk about in your book? [00:13:37] How have databases transformed from the time you started working on it? [00:29:31] What would be the first thing you do to help your organization start on a path to creating a Data strategy? [00:46:02] Random Round [00:46:07] It's one hundred years in the future. What do you want to be remembered for? [00:47:22] When do you think the first video to hit one trillion views on YouTube. Will happen and what will it be about? [00:48:41] So what are you currently reading? [00:48:57 What's something that you watch recently? [00:50:36] What about music? What do you got on repeat? [00:51:15] What makes you cry? [00:56:10] What talent would you show off in a talent show? [00:58:28] What are you interested in that most people haven't heard of? [00:58:43] What's your earliest memory? Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Watch the video of this episode: https://youtu.be/2rKppfByI5c Resources: https://datascienceharp.medium.com/i-thought-failure-was-my-destiny-until-i-realized-it-made-me-who-i-am-today-1a8bd4ccb1e2 https://dev.to/arslan_ah/grokking-leetcode-a-smarter-way-to-prepare-for-coding-interviews-5d9d https://fs.blog/mental-models/ https://github.com/jwasham/coding-interview-university https://juniortosenior.io/ https://vinvashishta.substack.com/p/assessing-a-data-scientists-coding https://www.jefflichronicles.com/mental-models https://youtu.be/4Qta0MyEoYU Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Watch the video of this episode: https://youtu.be/SButPV_V2-A Memorable Quotes from the Episode: [00:20:38] Most of the identifiers that associate a transaction with a person are just a series of letters and numbers, so it's not easy to trace back that Jonathan has sent Harpreet Sahota 1000 or 1000 bitcoin or something, but you can see all the transactions from the very, very beginning and you can export it. You could, you know, any number of data analytics products that you could run against it, just like any data store. One hundred percent, you can affect the data and get right to it, but you can obviously read and if you export it, you can do anything with it. Highlights of the Show: [00:00:40] Guest Introduction [00:02:58] Talk to us a bit about where you grew up and what it was like there. [00:06:14] How did this love of technology kick-off? How did you get interested in it? [00:09:15] What is a blockchain and how is this different from what we're used to seeing in Data structures? [00:15:05] Every time I hear about blockchain in the same sentence, almost they talk about cryptocurrency. So the exact same thing, or can we use them in place of each other? How does this work? [00:21:35] What are the implications of blockchain technology for data governance data management? [00:27:02] What is the difference between public permissioned and private blockchains. [00:45:42] Randon Round. [00:45:52] What's your favorite piece of clothing that you own? [00:46:13] Who are some of your heroes? Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Watch the video of this episode: https://youtu.be/035XW6k-Kls 00:00:31 Harpreet's Year End Message Regular Episodes Recap The Most Internationally listened to episode: https://youtu.be/-5EBk43uWD4 00:04:30 The Smartest Person in the Room | Christian Espinosa 00:05:36 Clearer, Closer, Better | Emily Balcetis 00:06:30 Meditations on Power and Mastery | Robert Greene 00:08:09 Pulling the Grim Trigger | Kevin Zollman 00:08:27 Your Job Doesn't Define YOU | Eleanor Tweddell 00:08:45 Explainable Data Science | Denis Rothman 00:09:03 Choose Who You Become | Chase Caprio 00:09:24 Your Beliefs Aren't Reality | Dave Gray 00:09:58 How to build a Data Science Culture | John K Thompson 00:10:51 Data Science Thunder From Down Under | Steve Nouri 00:11:55 The Philosophy of Sentientism | Jamie Woodhouse 00:12:42 The Shape of Geometry | Jordan Ellenberg 00:13:09 Our Nearest Neighbour | Ken Jee 00:13:40 Learning How To Learn | Barbara Oakley 00:14:04 Skip the Line |James Altucher 00:14:20 How to think like a data science billionaire | John Sviokla 00:15:02 Do What You Love Doing | Lillian Pierson 00:15:46 The Tesstimony | Jonathan Tesser 00:16:33 The Fearless Factor | Jacqueline Wales 00:16:56 Simplify Complexity | David Benjamin 00:17:22 Cultivate Your Rest Ethic | Max Frenzel 00:17:51 The Complete Man | Purdeep Sangha 00:18:26 Tales of a Data Engineer | Dennis Will 00:18:47 Subliminal Motives | Eric Okon 00:19:12 Become a Pragmatic Data Scientist | Andy Hunt 00:20:10 Turn the Lights on Data | George Firican 00:20:47 Give Your Brain Some Space | Tiffany Shlain 00:21:52 Wellness for Data Professionals | Madison Schott 00:22:24 The Industrial Philosopher | Cristina Digiacomo 00:23:05 Turn Ideas into Gold | Steven Cardinale 00:23:37 NLP and Philosophy | Kourosh Alizedah 00:24:17 The Book of Why | Dana Mackenzie 00:24:49 The International Woman of Data - Christina Stathopoulos The Happy Hours Recap 00:25:40 Question/Answer and Mentoring 00:26:26 What title should be written on the resume? 00:30:44 Sharing the hot seat with friends of the show! 00:31:38 What is the best way to break into research? 00:32:45 How to organize while working? 00:33:19 When will Linkedin content creators start making money? 00:33:47 What's up with the billion hours of YouTube video KPI? Having Fun 00:36:07 Jeff Li's freestyle rap session! 00:36:56 Insights with Eric 00:37:45 What is the perspective of Data on social media? 00:38:58 Credits Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Watch the video of this episode: https://youtu.be/82m6j8ZJgPI Resources: https://www.moreintelligent.ai/10kcasts/ Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Watch the video of this episode: https://youtu.be/7YhEjJFkRjI Resources: https://apps.ankiweb.net https://github.com/jeffmli/data-science-deliberate-practice https://www.amazon.com/Interpretable-Machine-Learning-Python-hands-ebook/dp/B08PDFXXRL/ref=zgbs169771740117?encoding=UTF8&psc=1&refRID=3TCSJQCA9WPJ5601MEG1 Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Watch the video of this episode: https://youtu.be/SWSLiGmnpao Find Dana Mackenzie online: https://danamackenzie.com https://scholar.google.com/citations?user=sQhKQ5cAAAAJ&hl=en Memorable Quotes from the Episode: [00:20:28] "At one point he realized something very fundamental and remarkable, which is if you switch the fathers and sons and you plot the sons side as the independent variable and the other side is independent variable, you get the same thing, you get the same fuzzy thing and you get the same correlation. And so correlation is something that is completely independent of causation." Highlights of the Show: [00:01:22] Guest Introduction. [00:03:02] Where you grew up and what it was like there? [00:04:23] As a kid, you loved writing, but then you ended up studying math at like the highest levels. Was that something that you foresaw happening? Were you always into math? Was it like a choice between math and writing? How did this play out? [00:10:13] if anybody who wants to develop and flex writing muscle, do you have any tips for them on how they can develop and cultivate this skill? [00:14:18] In view of your book "The book of Why", what is this computational cognitive faculty that humans certainly acquired that our chimpanzee cousins did not? [00:17:28] Concept of counterfactuals. [00:24:48] "Every statistics book says correlation is not causation. And they forget to tell you what is causation." [00:41:55] What is the ladder of causation? [00:48:57] "Smoking causes cancer", discuss. [01:01:11] What is the do operator all about? What makes it so revolutionary and special? [01:16:00] It is one hundred years in the future. What do you want to be remembered for? [01:17:58] What are you currently reading? [01:21:13] What song do you have on repeat? [01:25:29] What is one of your favorite comfort food comfort foods? [01:25:53] What have you created that you are most proud of? [01:26:03] Who inspires you to be better? Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: YouTube: https://www.youtube.com/c/TheArtistsofDataScience Instagram: https://www.instagram.com/theartistsofdatascience/ Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/ArtistsOfData

Watch the video of this episode: https://www.youtube.com/watch?v=wjueYMuS7kw Resources: https://calendly.com/harpreet-comet-ml/30min https://cloud.google.com/architecture/mlops-continuous-delivery-and-automation-pipelines-in-machine-learning https://cloud.google.com/architecture?doctype=concept%2Creferencearchitecture https://craftinginterpreters.com/ https://fullstackdeeplearning.com/spring2021/lecture-11/ https://kubernetes.io/blog/2020/12/02/dockershim-faq/ https://kubernetes.io/blog/2020/12/02/dont-panic-kubernetes-and-docker/ https://missing.csail.mit.edu/2020/version-control/ https://theartistsofdatascience.fireside.fm/kurtis-pykes https://www.amazon.ca/Software-Architecture-Trade-Off-Distributed-Architectures/dp/1492086894 https://www.youtube.com/watch?v=a6kqyqTNJM4&list=PLhr1KZpdzukdeX8mQ2qO73bg6UKQHYsHb https://youtube.com/playlist?list=PLhr1KZpdzukdeX8mQ2qO73bg6UKQHYsHb Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: YouTube: https://www.youtube.com/c/HarpreetSahotaTheArtistsofDataScience Instagram: https://www.instagram.com/datascienceharp Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/datascienceharp

Watch the video of this episode: https://youtu.be/AAAV0wOLqQo Find Christian Espinosa online: https://christianespinosa.com/ https://www.linkedin.com/in/christianespinosa/ Memorable Quotes from the Episode: [00:24:58] "...the final step is Kaizen. Kaizen is a is a Japanese word that means constant and never ending improvement with any of the six steps prior or the entire methodology. It's a journey, and you're not going to perfect it right out. The gate is taking this first step and the next step and the next step, and then making improvements as you move along. So that's the seven steps to the secure methodology." Highlights of the Show: [00:01:15] Guest Introduction. [00:02:43] Where you grew up and what it was like there? [00:05:43] Does Christian has the crazy interest to climb mountains? [00:06:13] When you're growing up as a kid man, did you ever think that you'd be this crazy ultra marathon running Iron Man, mountain climbing cybercriminal fighting awesome individual? [00:06:48] Where does that self rigor to be able to want to put yourself through these really challenging types of situation come from? [00:09:19] What does it mean to be the smartest person in the room? What does that mean to you and when is it a bad thing? [00:12:33] Is there a correlation or a relationship between the need to be the smartest person in the room and having like a fixed mindset? [00:14:14] Who are these "paper tigers" and why are they so dangerous? [00:19:20] How can you tell that somebody knows what their 'why' is? How do you assess for fit against a cultural fit? [00:20:53] What is "secure methodology"? What are the seven steps involved in it? [00:31:08] Do you think it's possible to identify whether we have a real growth mindset or a false one? [00:33:02] Being congruent with your belief and the philosophy behind growth mindset. [00:33:57] What are these NLP presuppositions in the context of your secure methodology? [00:35:00] What are your top two favorite presuppositions for the communication part of the security framework? [00:39:49] What is mono tasking? [00:43:17] What are some of the NLP presuppositions that we can use to remind ourselves that it is time to get down to to multitasking? [00:45:28] What are a couple of presuppositions that we should have in mind for the Kaisen? [00:46:38-00:46:38] Talk to us about the four phases of kaizen. [00:50:57] It is one hundred years in the future. What do you want to be remembered for? [00:51:37] Random Round. [00:51:37] When do you think the first video to hit one trillion views on YouTube will happen and what will it be about? [00:52:11] What do most people think within the first few seconds of meeting you for the first time? [00:52:41] What are you currently reading? [00:53:35] What song do you currently have on repeat? [00:53:59] What's your earliest memory? [00:54:32] When was the last time you changed your opinion about something major? [00:55:37] What's the best piece of advice you have ever received? [00:56:29] What's the right way going about finding a mentor in your experience? [00:59:01] Who was your favorite teacher and why? Don't forget to register for regular office hours by The Artists of Data Science: http://bit.ly/adsoh Register for Sunday Sessions here: http://bit.ly/comet-ml-oh Listen to the latest episode: https://player.fireside.fm/v2/eac-KT9/latest?theme=dark The Artists of Data Science Social links: YouTube: https://www.youtube.com/c/TheArtistsofDataScience Instagram: https://www.instagram.com/theartistsofdatascience/ Facebook https://facebook.com/TheArtistsOfDataScience Twitter: https://twitter.com/ArtistsOfData