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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
Dave on Data | David Langer

Dave on Data | David Langer

2022-05-1301:01:06

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
Comments (2)

sarvenaz td

Amazing episode! Really motivational. Thank you.

Feb 8th
Reply (1)
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