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The Artists of Data Science

Author: Harpreet Sahota

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In his book, "Linchpin", Seth Godin says that "Artists are people with a genius for finding a new answer, a new connection, or a new way of getting things done."
Does that sound like you?
If so, welcome to The Artists of Data Science podcast! The ONLY self-development podcast for data scientists.
You're here because you want to develop, grow, and flourish.
How will this podcast help you do that?
Simple.
By sharing advice on how to :
- Develop in your professional life by getting you advice from the best and brightest leaders in tech
- Grow in your personal life by talking to the leading experts on personal development
- Stay informed on the latest happenings in the industry
- Understand how data science affects the world around us, the good and the bad
- Appreciate the implications of ethics in our field by speaking with philosophers and ethicists
The purpose of this podcast is clear: to make you a well-rounded data scientist. To transform you from aspirant to practitioner to leader. A data scientist that thinks beyond the technicalities of data, and understands the impact you play in our modern world.
Are you up for that? Is that what you want to become?
If so, hit play on any episode and let's turn you into an Artist of Data Science!
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Nir Bashan is a world-renowned creativity expert. He has taught thousands of leaders and individuals across the globe how to harness the power of creativity to improve profitability, increase sales and ultimately create more meaning in their work. FIND NIR ONLINE Website: https://www.nirbashan.com/ LinkedIn: https://www.linkedin.com/in/nirbashan/ Twitter: https://twitter.com/Nir_Bashan QUOTES [00:05:42] "I wanted to be insanely creative, like some of my heroes and and I noticed that they had a technique, all of them a little bit different, but they all had some technique. And it turns out that that technique makes them no different than you or I or anybody listening to this podcast. And it makes them no different. It's all about coming up with that creativity and learning how to harness it and repeating it and pulling it out whenever you need." [00:08:32] "We live in a society in a day and an age where we can get data on just about anything...But what does it do to have that data? If we're not able to make that information work for us, it's meaningless. " [00:12:42] "We've gotten so comfortable in modernity that we're looking for problems that don't exist" [00:17:00] "A good company and a good person on a career path is armed with creativity to be able to solve problems as they occur in new and different ways. And that really is the most important thing that we can do today to become relevant and to stay relevant and to stay successful." [00:22:49] "I feel that quantification is just the mere act of assigning a number to something and that is just not good enough anymore. It's not." [00:25:51] "The numbers aren't really telling us all that we need to know. There's got to be a different way. There's got to be a new way to look at those things. And that way is creativity." [00:39:25] "Creativity is a component of our DNA and who we are. And in order for us to really be fully evolved human beings, I think we need to balance our analytical drive with the creative drive" [00:53:41] "Egos kill creativity, just like the self-doubt or perhaps even more. We develop egos when we think that we know what will happen and when we think that we have some advantage that other people don't have." SHOW NOTES [00:01:52] Guest introduction [00:02:53] Nir’s journey and path to now [00:05:31] Being creative isn’t just for artists and musicians [00:07:42] Why is it that just having logic alone is not going to be enough to propel us to the next level? [00:10:09] How can a non-creative person discover their creativity and put that to work? Harpreet Sahota:[00:14:29] How has creativity impacted business acumen? [00:18:14] What are some of the practices of the of yesteryear that we need to get rid of to really be successful in the business of tomorrow? [00:21:30] Talking about quantification, can you just kind of make that concept concrete for us? What is it that that you mean when you say quantification? [00:25:24] How you’ve been educated out of the creator’s mindset [00:27:16] The Trinity of Creativity. [00:29:15] Why is it crucial that we shut out the analytical part of our mind? [00:32:56] What creativity means to Harp Nir Bashan: [00:35:06] Why you shouldn’t be afraid to ask “stupid” questions [00:38:12] The importance of being open and receptive and willing to wander off the path that you've paved for yourself [00:39:17] Emotional intelligence and creativity [00:41:04] Positivity and creativity [00:43:58] What questions can we ask ourselves when we’re coming up to a problem to make we frame these problems in more positive ways? [00:46:04] What are the personality traits of creativity? How do we cultivate those traits for ourselves? [00:48:24] How do we catch ourselves when we're having negative internal dialogs so that we can shift ourselves to have more of the cultivated personality traits for creativity? [00:51:24] Psychological safety and creativity [00:54:33] How do we fight something (the ego) that comes naturally to us? [00:55:51] The Four P’s of growth [00:57:10] Why discipline is a pathway to creativity [00:58:18] How we can use a creative mindset to be more creative with our time management? [00:59:36] It's one hundred years in the future: What do you want to be remembered for? [01:00:50] The Random Round Special Guest: Nir Bashan.
The Data Science Happy Hours keep getting happier! Guest's that came by: Thom Ives, Dave Langer, Giovanna Malaga, Monica Kay Royal, and so many more! Check it out and don't forget to register for future office hours: http://bit.ly/adsoh If you want to interact with me multiple times a week, join Data Science Dream Job for 70% off: http://dsdj.co/artists70 Watch the episode on YouTube here: https://www.youtube.com/playlist?list=PLx-pFwty92wJoWzoO7WlfaM7iYB8qjm We were voted one of the top ten data science podcasts by FeedSpot - check it out here: https://blog.feedspot.com/datasciencepodcasts/ Checkout Nicole's article shouting out the show: https://towardsdatascience.com/supercharge-data-science-3da3ccf103-13da3ccf103 I was on the Rising Laterally Podcast, check it out here: https://www.youtube.com/watch?v=cz6SpTi7tLc SHOW NOTES [00:04:28] New to data science, trying to get to work experience, and need some tips [00:08:04] How do I find out what problems data scientists solving in various industries? [00:11:03] How to stay up on trends in the industry [00:12:52] How to understand what the business needs [00:14:52] One of the most interesting hires Joe made was a 19 year old punk rocker [00:16:07] Have more than just technical virtuosity [00:17:35] How to go from academia to industry [00:20:07] What challenges do you see somebody facing coming from an academic background that primarily uses R in that research setting to somebody who's going to be using it in a business type of role? [00:21:41] How to get hired at Amazon [00:22:49] Speaking of getting a job at Amazon, LinkedIn top twenty twenty cockier is actually an employee of Amazon. So what does someone need to do to get a job at Amazon? [00:25:30] Your previous work experience can still benefit you [00:26:35] Do you need a masters in to be a data scientist? [00:30:21] Don’t lead a life of meeting spec [00:33:58] Books to get business intuition [00:35:08] I just completed a masters in math, do I need to do a bootcamp? [00:38:30] Some great recommendations for SQL each project. [00:41:08] I'd like to get my management onboard into automating data integration and consistent dashboards. Do you have any specific suggestions for what goes into the elevator pitch to management over? [00:44:56] How to get ETL experience when you already know SQL [00:47:39] A question on text analytics [00:51:35] How much big data knowledge do I need? [00:54:39] What do you think is causing the shift back to the data warehouse? [00:57:08] Which book should I read to get up to speed on production ready code? [00:58:57] How do I choose the right data and how do I solve a problem? [01:01:08] Greg asks an awesome question about costs and benefits of automation [01:07:39] What makes a good data scientist?
Jeff Kreisler uses behavioral science, real life, and humor to understand, explain, and change the world. He’s pretty much your friendly, typical Princeton educated lawyer turned award-winning comedian, best-selling author, and champion for behavioral economics . WHAT YOU'LL LEARN What money is, why we won't make good money decisions, the common cognitive biases we have related to money, how to not let the retailers dupe you during this holiday shopping season, and more! QUOTES [11:31] "Traditional economics says everything's cost benefit analysis. Reality is that that's not how it works. We are busy people. We have a lot of stress and we don't always make the rational choice." [16:47] "The there's no clear right or wrong choice with money that we all always know. There's always some uncertainty. And when uncertainty is in any decision, that gap gets filled by the emotional needs that we have. The need to feel like we're making the right choice. The need to feel like we've done the right thing. The need to feel good. And that's when we can be prone to make irrational decisions, because we go by our feelings and emotions. " [18:08] "I feel like marrying the data science with the people science is going to be like an incredible combination. To not just know where they're going and what buttons to push, but why why are people doing this?" [20:30] "When we pay for something, it stimulates the same region of our brain as physical pain. And that pain should serve a purpose. It should make us stop and think about what we're doing." [34:01] "You can't pay your rent with the money you save shopping." FIND JEFF ONLINE Website: http://www.jeffkreisler.com/ LinkedIn: https://www.linkedin.com/in/jeffkreisler/ SHOW NOTES [00:01:32] Introduction for our guest [00:02:42] We talk about Jeff’s journey [00:08:06] How Jeff teamed up with Dan Ariely [00:13:54] The concept of money [00:18:46] Mental shortcuts and money [00:22:24] What would you do with $30,000 [00:25:24] Relativity, money, and why we suck at comparing things [00:29:38] System 1 and System 2 [00:31:33] Don’t fall for the sale price! [00:33:22] How retailers will trick you with discounts [00:35:52] The anchoring effect [00:41:16] Mental accounting [00:45:06] Extreme examples of mental accounting [00:46:38] Do we have the same cognitive biases for other people's money as we do for our own? [00:48:39] Herding and self-herding [00:52:28] Jeff shares his top three favorite tips for fighting our flawed financial thinking [00:56:37] Some other cognitive biases to watch out for this holiday shopping season [00:58:27] It's one hundred years in the future. What do you want to be remembered for? [00:59:23] The random round Special Guest: Jeff Kreisler.
The tenth episode of the Data Science Happy Hours were popping off! Guest's that came by: Thom Ives, Dave Langer, Ben Taylor, Sarah Nooravi, Giovanna Malaga, Monica Kay Royal, Kate Strachnyi, Carlos Mercado, and so many more! Chat transcript: http://theartistsofdatascience.fireside.fm/articles/oh10-chat-transcript Huge thanks to our sponsor for this episode - Cloud Academy! Go to https://cloudacademy.com/ and use the coupon code ARTIST for 50% off the monthly subscription fee for life! Check it out and don't forget to register for future office hours: http://bit.ly/adsoh If you want to interact with me multiple times a week, join Data Science Dream Job for 70% off: http://dsdj.co/artists70 Watch the episode on YouTube here: https://www.youtube.com/playlist?list=PLx-pFwty92wJoWzoO7WlfaM7iYB8qjm We were voted one of the top ten data science podcasts by FeedSpot - check it out here: https://blog.feedspot.com/datasciencepodcasts/ Checkout Nicole's article shouting out the show: https://towardsdatascience.com/supercharge-data-science-3da3ccf103-13da3ccf103 I was on the Rising Laterally Podcast, check it out here: https://www.youtube.com/watch?v=cz6SpTi7tLc SHOW NOTES [00:02:09] How would you define a full stack scientist? [00:04:18] Intrapreneurship: being the first data scientist in an organization [00:06:04] What not to do as a data scientist [00:07:19] Mistake in cross-validation [00:08:54] Building minimal viable products [00:10:19] “We're not earthlings, all of us on the screen. We are barely earthlings.” [00:12:31] One of the problems with machine learning [00:14:04] Screwing up things, the hard way. [00:15:43] What do you think about people starting as data analysts and then transitioning into a data scientist, or is there a better way of doing that? [00:19:01] “I actually have something against titles themselves. In some cases, they're not what they seem.” [00:21:04] “You have to be skeptical of job descriptions. You have to be skeptical of titles.” [00:24:11] “How you present your skills is an important way of how they are going to consider you for their position.” [00:28:06] Do mock interviews [00:28:45] Take the beginner stuff off your resume [00:30:56] WTF is a unit test and when do I need them? [00:33:24] The rule of thumb for knowing when you need to do unit tests [00:33:35] “But it's not technical debt if the debt doesn't come due” [00:35:00] Is there going to be a shortage of business domain experts in data science? [00:41:27] “At the end of the day, Data analyst, data scientist, the main point that you're trying to do is to solve a problem, to help the business be better, make more money, get more customers.” [00:42:43] Can you give some input on how you manage your time? [00:44:06] How Sarah Nooravi manages her time [00:45:41] How Giovanna manages her time [00:47:35] How Harpreet manages his time [00:48:36] How Ben Taylor manages his time [00:50:07] Carlos says the most un-Carlos thing ever: “Listen to your body” [00:51:01] How Dave Langer manages his time [00:52:12] A summary of how to manage time [00:53:41] Network analytics? [00:55:15] Learn to build, learn to sell…if you can do both, you will be unstoppable [00:58:11] Test driven development and data engineering [01:02:44] What are some things that data scientist are not good at, but they probably should start getting good at? [01:07:33] The importance of curiosity Special Guest: Carlos Mercado.
Maya is a marketing executive, blogger, speaker, podcaster, and a career coach. She’s worked for companies like Microsoft and Google, racking up multiple promotions and raises, and strategically leveling up from an individual contributor to vice president. She’s blended her experience climbing the corporate ladder, motivational leadership style, authentic voice, and love for helping others into a book designed to give you the tools you need to succeed! FIND MAYA ONLINE Website: https://www.mayagrossman.com/ LinkedIn: https://www.linkedin.com/in/mayagrossman/ Twitter: https://twitter.com/mayagrosmn WHAT YOU'LL LEARN [00:14:38] The Owner’s Mindset [00:41:48] The influence formula [00:43:36] How Maya stopped a plane from taking off [00:45:08] How to tell stories with data [00:47:37] Talent stacking [01:00:55] The top five skills you need to survive the next decade [01:01:47] How to ace an interview QUOTES [11:37] "Invaluable is all about mindset." [12:39] "We've had research for more than one hundred years that shows us that career success is best predicted by soft skills. Seventy five percent of your success can be predicted by our soft skills and only twenty five percent by your hard skills or your profession. And even though we know this, there's so little information about how to actually acquire soft skills." [15:37] "You need to look at the bigger picture. You need to think like an owner, which means you want to make sure that you get the most out of everything that you do, and you spend the least" [19:32] "You need to understand that no matter how small your role is, you are part of a bigger machine. You're part of the company and your job is to make that company successful, however you can. And the minute you realize that, you're going to start seeing opportunities to do more and to help more and in most cases, that's going to give you more experience. You can experiment and see what you like, what you don't like. And it's also a great way to set yourself up for a promotion or for your next role." [24:12] "Because if you don't learn and you don't grow, you're basically moving backward. And it's kind of weird. Most people don't read a book after they graduate from college. As we grow up, we were being taught that you need to learn. So you go to school if you're like you go to college. But the minute that ends, there's no motivation to continue learning." [28:38] "It's not just someone who gets things done. It's someone who has the ability to identify a problem. They care enough to ask questions, to dig around, to actually take action when they come across something that doesn't work." [33:17] "If you're a lateral thinker, you're able to take information from different areas, different disciplines, different things you've done in your life, and apply them to come up with a very creative idea." [01:03:08] " I have 15 years of experience and my resume is not two pages long. So if you're early in your career, you do not need twenty thousand bullet points. Less is actually more." SHOW NOTES [00:01:35] Introduction for our guest [00:02:44] Maya talk to us about her upbringing [00:04:29] What Maya loves about marketing [00:05:36] How all of Maya’s experience culminated in a book [00:06:58] What was the process like for you writing the book? [00:08:21] What is invaluable all about? What does that mean? [00:10:08] Who is that person that you're writing this book for? [00:11:21] Is it ever too late to become invaluable? [00:12:33] What is the deal with soft skills and why are they so important? [00:14:38] The Owner’s Mindset [00:16:49] How do we start cultivating this owner's mindset? [00:20:03] What can we do to help develop a sense of purpose for ourselves and our work? [00:22:56] The craftsman mindset [00:23:39] Why you need to be a lifelong learner [00:24:48] How can we turn learning into a habit? [00:27:32] What are some newsletters that you are currently subscribed to? [00:28:10] What is a fixer? [00:31:33] Helping budding fixer’s climb the ranks [00:32:34] The importance of lateral thinking [00:35:18] Never let your fear decide your fate [00:37:19] Cultivating psychological safety [00:41:48] The influence formula [00:43:36] How Maya stopped a plane from taking off [00:45:08] How to tell stories with data [00:47:37] Talent stacking [00:53:20] The five pieces of career advice that Maya wishes somebody would have given her in her twenties. [00:55:41] Tips for networking [01:00:55] The top five skills you need to survive the next decade [01:01:47] How to ace an interview [01:05:51] Negotiations [01:08:39] Advice for the women in our audience [01:10:23] Its one hundred years in the future. What is it that you want to be remembered for? [01:10:49] The Random Round Special Guest: Maya Grossman.
Thom Ives, David Knickerbocker, and Carlos Mercado join in on the fun! Huge thanks to our sponsor for this episode - Cloud Academy! Go to https://cloudacademy.com/ and use the coupon code ARTIST for 50% off the monthly subscription fee for life! Check it out and don't forget to register for future office hours: http://bit.ly/adsoh If you want to interact with me multiple times a week, join Data Science Dream Job for 70% off: http://dsdj.co/artists70 Watch the episode on YouTube here: https://www.youtube.com/playlist?list=PLx-pFwty92wJoWzoO7WlfaM7iYB8qjm We were voted one of the top ten data science podcasts by FeedSpot - check it out here: https://blog.feedspot.com/datasciencepodcasts/ Checkout Nicole's article shouting out the show: https://towardsdatascience.com/supercharge-data-science-3da3ccf103-13da3ccf103 [00:04:05] “I haven’t gotten a job in months, what should I learn next to get a job?” [00:05:39] Follow your own obsession [00:09:44] What to do when you feel like your brain is getting fried from everything you’re learning [00:11:29] Carlos joins in – “Start from the bottom” [00:12:53] Don’t worry about your title [00:15:18] How to get data science experience without having a data science job [00:18:11] David talks about the hype cycle he’s experienced through his career [00:19:40] How to balance your learning [00:22:10] Why you should speak your mind [00:25:01] Thom says a four letter word [00:28:50] Eric comes in with a question that has us stumped for a little bit [00:29:41] Balancing datasets [00:31:32] Rare events [00:35:13] Hyperparameter what? [00:36:15] The issue with random seeds [00:40:31] Thom compliments Eric on sharing his knowledge [00:41:55] Where’s everyone joining in from? [00:46:07] Diversity and representation is important and welcome [00:47:33] Correlation and causation [00:53:07] The importance of critical thinking [00:56:39] David gets into network theory [00:58:11] Functional vs OOP design principles in production [01:00:16] “I want production to be beautiful.” – David Knickerbocker [01:02:04] Network analysis Special Guest: Carlos Mercado.
Sadie is helping pave the way for women in data science as being the first female instructor for Data Science on the Coursera platform, and as founder and CEO of Women in Data - a non-profit organization focused on increasing diversity in data careers. FIND SADIE ONLINE Website: http://sadiestlawrence.com/ LinkedIn: https://www.linkedin.com/in/sadiestlawrence/ Instagram: https://www.instagram.com/sadiestlawrence Twitter: https://twitter.com/sadiestlawrence QUOTES [18:59] "If you're looking to get into Data science and transitioning from something else, what made you successful in that area and what principles did you apply?" [20:41] "I knew that if I was going to do Data science, I needed a community and a tribe of people to be a part of." [22:54] "Data science isn't just about building models and doing that type of work. You're working, usually for, a business..." [34:18] "If you want to own your career, really what you need to do is look at and see what things can I control in my life. And when you start hundred percent focusing on those the world around you is going to change." SHOW NOTES [00:00:40] Guest introduction [00:03:19] Sadie’s path to data science [00:05:52] Data collection in laboratory settings [00:07:32] The data science hype [00:08:24] Is data science going away any time soon? [00:09:39] The positive impact data science will have [00:11:34] Going from good to great as a data scientist [00:14:02] SQL skills you need for data science [00:17:23] An action plan for breaking into data science [00:22:02] Soft skills to elevate your career [00:23:19] Use verbal judo to be more persuasive [00:24:46] How to communicate with executives [00:25:55] The data science mindset [00:27:35] Making the most of networking events [00:29:24] Communication and teamwork [00:30:49] Is data science an art or science? [00:32:55] How to own your career [00:36:38] Steps for combating imposter syndrome? [00:38:17] Tips for women in data science [00:43:45] What can the Data community do to help foster the inclusion of women in the field? [00:45:31] What's the one thing you want people to learn from your story? [00:46:43] Lightning round Special Guest: Sadie St. Lawrence.
We have a surprise visit from friend of the podcast, Srivatsan Srinivasan! Lot's of awesome topics covered in this office hour session! Huge thanks to our sponsor for this episode - Cloud Academy! Go to https://cloudacademy.com/ and use the coupon code ARTIST for 50% off the monthly subscription fee for life! Check it out and don't forget to register for future office hours: http://bit.ly/adsoh If you want to interact with me multiple times a week, join Data Science Dream Job for 70% off: http://dsdj.co/artists70 Watch the episode on YouTube here: https://www.youtube.com/playlist?list=PLx-pFwty92wJoWzoO7WlfaM7iYB8qjm We were voted one of the top ten data science podcasts by FeedSpot - check it out here: https://blog.feedspot.com/datasciencepodcasts/ Checkout Nicole's article shouting out the show: https://towardsdatascience.com/supercharge-data-science-3da3ccf103-13da3ccf103 NOTES [00:01:57] Use your Excel skills to learn python [00:04:35] Automating stuff you do in Excel with python [00:06:49] Srivatsan shares tips on complementing your Excel skills with python [00:08:38] Some resources recommendations for learning python [00:10:34] How to find out what niche in data science to pursue [00:15:17] The main problem with graduate level education in data science [00:15:33] How the real world is different from Kaggle [00:17:27] How to broaden your skillset [00:19:47] Ideas for a data engineering project [00:21:56] What are people looking for in interviews? [00:24:50] Talking about portfolio projects in interviews [00:27:23] Think about the question behind the question in an interview [00:34:13] How Srivatsan comes up with new topics for his YouTube channel [00:36:08] The importance of understanding the basics [00:38:10] We talk about SQL [00:42:37] Real world experience beyond the workplace [00:44:47] Common SQL questions in an interview [00:49:57] Don’t undersell yourself in an interview [00:50:21] Storytelling in data science [00:57:37] Is a Masters programs in data analytics, data science and/or computer science valuable? [01:00:21] Finding datasets for projects Special Guests: Nicole Janeway Bills and Srivatsan Srinivasan.
Annie Duke is a is a poker champion turned author, consultant, and corporate speaker whose here to teach us how to get comfortable with uncertainty and make better decisions. WHAT YOU'LL LEARN We go deep into Annie's books: Thinking in Bets and How to Decide. By the end of this episode you'll have a set of tools to help you in your decision making process. And you'll also get some insight into why the election doesn't go the way you thought it would! FIND ANNIE ONLINE Website: https://www.annieduke.com/ Twitter: https://twitter.com/annieduke LinkedIn: https://www.linkedin.com/in/annie-duke-30ab2b5/ QUOTES [12:25] "Betting is basically saying I have some set of limited resources that I can invest in to and I'm choosing among options where how that option turns out is not deterministic. It's probabilistic." [15:09] "...And whichever one you choose is just a prediction of which one's more likely to produce a happier version of you in the future." [16:25] "We're living in a probabilistic world, meaning that there are very few decisions that you can make that are guaranteed to have one single outcome." [20:14] "But presidential campaigns actually happen over quite a long period of time...Can you think of anything? Where in real time, people are analyzing the decisions that are being made more than a national presidential election." [26:10] "Our brains really like to make a create a narrative that makes sense where one thing leads to another and kind of an orderly fashion. We really aren't comfortable with randomness." [28:19] "So luck is intervening between the decisions that you make, the option that you choose, and the particular outcome that you happen to observe." [32:43] "I also don't know a lot of stuff. The way to solve for that is to go explore the universe of stuff that I don't know, and to explore that in a really objective way. Where I'm kind of like maximizing my ability to run into information that is different than the things that I believe to be true,." [39:40] "Well, smart people are just better at spinning narratives. They're better at looking at a set of data and interpreting that data to fit the model that they already have. That's just why it's just like this kind of narrative spinning that's kind of going on in our heads." [01:01:58] "It's not that imagining failure causes failure. It's that imagining failure causes success, because if you imagine failure, you can see all the obstacles that might be lying in your path and then you can actually do something about them before you run into the obstacle" SHOW NOTES [00:01:32] Guest introduction [00:03:00] How Annie became the “Duchess of Poker” [00:04:09] What Annie’s hometown was like [00:07:44] What high school was like for Annie [00:09:59] How Annie’s experiences led to writing her books [00:12:07] What are bets, what are decisions and what's the relationship between them? [00:16:06] The perils of “resulting” [00:17:45] Why you shouldn’t equate decision quality with outcome quality [00:20:14] Decisions and elections [00:24:19] Why our brains are not built for rationality [00:26:10] Why our brains need narrative [00:30:50] Your beliefs have two major weaknesses [00:35:48] Why being smarter makes you more susceptible to motivated reasoning [00:40:48] The decision multiverse [00:44:29] Your good outcomes aren’t always a result of good decision making [00:48:10] How Thinking in Bets changed my life and a case study of Bayesian psychology in the job search process [00:53:42] Dealing with things that are not in your control [00:55:46] The pre-mortem [00:59:01] The power of negative visualization [01:03:36] The influence of Stoic philosophy on Annie’s work [01:04:02] A dude in a basement has a hypothesis… [01:04:29] Positive thinking and the Reticular Activating System [01:08:07] The Alliance for Decision Education. [01:09:56] We’re not teaching kids the things they really need to know [01:14:41] It’s one hundred years in the future - what do you want to be remembered for? [01:15:01] The random round Special Guest: Annie Duke.
Machine Learning legend Vin Vashishta swings by office hour to chat! Tonnes of awesome insight into what the future of data science is going to look like, why feature engineering can be dangerous, why a model is a hypothesis, and more! Huge thanks to our sponsor for this episode - Cloud Academy! Go to https://cloudacademy.com/ and use the coupon code ARTIST for 50% off the monthly subscription fee for life! [00:03:54] What I do as a mentor at DSDJ [00:10:56] Vin’s perspective on the data science job market due to COVID [00:14:09] Is data science going out of fashion? [00:16:55] The two types of data scientists out there, one of them won’t survive [00:21:50] You know, it's funny. It's got to be monitoring and production notes and stuff. [00:23:25] Question on a project that an attendee was working on – clustering and topic modeling [00:27:27] Saving models (to serve later) [00:32:02] Is analytics data science? [00:35:13] A philosophy less on feature engineering. [00:40:45] Old school data mining and feature engineering [00:46:02] You must validate your model [00:55:15] Why is a model a hypothesis [00:59:08] The importance of experimenting [01:04:37] Is it ever OK to build a biased model? [01:08:59] Preventing bad biases [01:10:54] A philosophy of modeling [01:15:24] Do we rule out deep learning? Check it out and don't forget to register for future office hours: http://bit.ly/adsoh If you want to interact with me multiple times a week, join Data Science Dream Job for 70% off: http://dsdj.co/artists70 Watch the episode on YouTube here: https://www.youtube.com/playlist?list=PLx-pFwty92wJoWzoO7WlfaM7iYB8qjm We were voted one of the top ten data science podcasts by FeedSpot - check it out here: https://blog.feedspot.com/datasciencepodcasts/ I was on the Human Prosperity podcast, check it out here: https://www.youtube.com/watch?v=RbD3aV2TfKk Special Guest: Vin Vashishta.
Sean Derrig is NOT an eco-warrior, he’s a scientist. And he’s on a mission. He’s also the author of a wildly entertaining and informative blog called Rectofossal Ambiguity - where he takes on the alter ego RectoFossa, a grumpy microbiologist who thinks writing this blog might be an antidote to all The Stupid on the internet. Recto Fossa is latin for arsehole, apparently. Huge thanks to our sponsor for this episode - Cloud Academy! Go to https://cloudacademy.com/ and use the coupon code ARTIST for 50% off the monthly subscription fee for life! FIND SEAN ONLINE LinkedIn: https://www.linkedin.com/in/seanderrig/ Website/Blog: https://rectofossal.com/ QUOTES [00:20:59] "So biologists, we're all obsessed with shit, basically. Especially microbiologists." [58:32] "You need to understand that your success is entirely wrapped up in how successful you can make your team. It's not about you. It's about the people you put around you and what you can do to make them truly successful. And that's what you got your success from, because the company isn't going to grow based on finding your own ego. It just it doesn't - it would be great if it did. It would be marvelous. But life life doesn't work like that." [01:00:17] "And without the ego and the drive of the lunatic at the helm, things don't happen. However, you do need somebody with their eye on the brakes and an eye on the cliff that you're hurtling towards, as well as." [01:03:56] "I'd say just keep canceling the bullshit out there. Let's get the good studies out there and make sure that people understand what they mean and what they don't. And in terms of science communication, what you need to suss out really quickly is the level you need to pitch something at" [01:05:11] "Either we can do this, which we think is quite a good idea, or we can hold our hands in a bucket of shit and give ourselves a huge round of applause. Which would you prefer to do? Well, I think I'll do the first one." [01:06:36] "One of the greatest advertising copywriters ever once said when you're writing it out, that's only 10 percent of people read beyond the first line. So you've blown 90 percent of your budget on the first sentence. Make it a fucking good one. And in that, I think sums it up, it's you need to make sure you grab their attention" [01:11:35] "I'm basically unemployable, and I haven't done too badly." [01:16:39] "You need to continually reinvent and improve yourself because there's always a superior model." [01:18:13] "There's just so much stuff out there that I don't know. I'm totally disappearing in a bubble of my own confirmation bias." [01:21:46] "If you're uncomfortable with gay marriage or opposite marriage, it's fine, you can be as uncomfortable with that as you want, just don't marry a gay person and it will never, ever, ever, ever affect you" SHOW NOTES [00:01:33] Guest Introduction [00:03:28] Sean’s journey to the dark side of microbiology [00:06:56] What's the dark side of microbiology? Sean Derrig: [00:09:18] 70 billion friendly bacteria [00:14:31] WTF is a “fatburg” [00:18:27] All the unexpected ways we’re wasting water [00:21:05] What is a radicle? [00:21:42] Debunking big pharma Sean Derrig: [00:23:36] The importance of good inclusion criteria [00:27:08] Biases in biological sciences [00:31:21] The importance of randomized trials [00:34:56] How to not bullshit yourself [00:38:34] Question everything [00:39:53] Bayes theorem and COVID testing [00:49:34] Which is worse for COVID testing: false positives or false negatives? [00:52:31] Sensitivity and specificity in COVID testing [00:53:35] Bayesian psychology [00:56:00] Tips for entrepreneurs [00:58:32] What success is all about [00:59:55] Traits of successful entrepreneurs [01:01:39] Entrepreneur in the COVID era [01:01:50] That would be kind of interesting inside. [01:04:52] How to communicate with executives in a way that will make them care [01:08:15] Sean talks about his patents [01:11:27] What's the one thing you want people to learn from your story? [01:12:02] Lightning round Special Guest: Sean Derrig.
Despite Max's outward success, he spent much of his life unmotivated and depressed. Struggling with bouts of frustrations, conflicts with others, relationship and career failures, he felt so unhappy he was contemplating suicide. He’s since taken on a journey of personal growth and development acquiring a brand new mindset and changing his relationship with himself, and those around him. Today he comes on the show to talk to us about data engineering and shares SEVERAL PRICELESS tips for productivity and happiness Huge thanks to our sponsor for this episode - Cloud Academy! Go to https://cloudacademy.com/ and use the coupon code ARTIST for 50% off the monthly subscription fee for life! FIND MAX ONLINE LinkedIn: https://www.linkedin.com/in/maxzheng/ The Life Guide on GitHub: https://github.com/maxzheng/great-life-guide Double Your Happiness Guide: http://double.guide I was Max's Human Prosperity podcast, check it out here: https://www.youtube.com/watch?v=RbD3aV2TfKk WHAT YOU'LL LEARN [07:00] The difference between data engineering and software engineering [08:46] The spectrum of data engineering [11:21] Tips for people transitioning from software engineering to data engineering [12:26] How to prepare for interviews in data engineering QUOTES [43:19] "And that applies to software development or data engineering work and things like that. So when you have a data project, make sure that you are actually working on a solid foundation. Don't just build everything as fast as just writing some script and then throw it out and be done with it because you have to maintain that goal. So you copy and paste a duplicate bunch of code everywhere. And that's a wrong thing, obviously." [55:18] "And that's one way of seeing it, because when you actually really look at it, a failure is simply something you don't know for now. And then once you do go through it and figure out what you don't know, you have learned something is a lesson in disguise." [58:00] "It's really important that we understand two or three aspect of memory and how it works. And one is that memory works based on association, so it's always associated with something that you already know. And if you try to remember something without associating something you to know, it'll be very hard" [01:06:29] "So loving yourself completely is to remove any shackles from you. Believe in yourself what you can actually use to push yourself forward. So and once you have this nothing holding you back, then you can run a full throttle" SHOW NOTES [00:01:34] Guest introduction [00:02:47] How did you get to where you are today in your career? [00:05:45] How’d you get into data engineering? [00:07:01] The key difference between software engineering and Data engineering? [00:08:46] Tips for transitioning from software engineering to data engineering [00:11:21] How to get hands-on data engineering experience [00:12:11] Tips for the job search process [00:15:38] How and why Max grew his LinkedIn network so quickly [00:17:16] How Max defeated his old self and emerged a stronger, better person [00:22:21] Depression hidden in plain sight [00:23:18] How Max started his new mission in life [00:29:36] The difference between being right and doing right [00:31:02] Four steps to being happy [00:33:50] The happiness framework [00:35:21] Nurture your drive [00:38:14] A framework for being more productive [00:46:08] Max helps me with my battle against distraction [00:50:02] What to do when you lose momentum and motivation [00:52:14] How to fight imposter syndrome [00:57:00] Choose your belief system [00:57:51] Tips to increase your memory [01:01:46] The importance of a growth mindset [01:05:58] What's the one thing you want people to learn from your story? [01:06:45] Lightning round Special Guest: Max Zheng.
Another awesome episode this week! Our friends Ashen, Navya, and Haseeb come back for some really insightful questions. We talk about whether you really need math skills in data science, how to answer the "what's your salary expectations" questions, a resume review, some ideas for data science projects, and our friends turn the tables and interview me...again! I really enjoyed this weeks session - tune in and let me know what you think: theartistsofdatascience@gmail.com. By the way you can email me anytime with any question and I promise I will respond! Huge thanks to our sponsor for this episode - Cloud Academy! Go to https://cloudacademy.com/ and use the coupon code ARTIST for 50% off the monthly subscription fee for life! If you want to interact with me multiple times a week, join Data Science Dream Job for 70% off: http://dsdj.co/artists70 Watch the episode on YouTube here: https://www.youtube.com/playlist?list=PLx-pFwty92wJoWzoO7WlfaM7iYB8qjm We were voted one of the top ten data science podcasts by FeedSpot - check it out here: https://blog.feedspot.com/datasciencepodcasts/ I was on the Human Prosperity podcast, check it out here: https://www.youtube.com/watch?v=RbD3aV2TfKk Check it out and don't forget to register for future office hours: http://bit.ly/adsoh
Carl is a former Wall Street Quant turned data scientist who is leading the battle against churn, using data as his weapon. A data scientist, he uses a variety of tools and techniques to analyze data around online systems, and his expertise has led to the creation of the Subscription Economy Index. Currently, he’s the Chief Data Scientist at Zuora - a comprehensive subscription management platform and newly public Silicon Valley “unicorn” with more than 1,000 customers worldwide. FIND CARL ONLINE Website: https://fightchurnwithdata.com/ LinkedIn: https://www.linkedin.com/in/carlgold/ Twitter: https://twitter.com/carl24k GitHub: https://github.com/carl24k WHAT YOU'LL LEARN [00:16:01] What is churn? [00:21:48] Metrics for understanding churn [00:24:01] Feature engineering for churn [00:27:22] Why ratio metrics are the best best in your battle against churn [00:33:09] Dealing with outliers [00:39:34] More feature engineering tips QUOTES [09:06] "When I started out, of course, people thought machine learning was trash...No one was that interested in machine learning back in the early 2000s. It wasn't until after Google essentially had showed how much they could do with machine learning in a production environment with big data." [12:22] "It should enable better decisions, too. Not just faster decisions by getting the right data to the right people and giving them the right tools. We really should see companies making more optimal decisions." [13:30] "There should be like a Hippocratic Oath for Data scientists, which means that goes beyond just you don't want to make mistakes. It means that you shouldn't be working on those, you know, on those dangerous applications. " [22:04] "the features that you choose in my mind are really the main part of solving any data science problem and not the algorithm. I show actually in my book that if you do a good job on your feature engineering, the algorithm that you choose is not that important for your accuracy. So feature engineering always has number one importance in Data science" SHOW NOTES [00:01:31] Introduction for our guest [00:02:54] Carl’s path into data science [00:04:30] The fascination with churn [00:08:04] How much more hyped do you think the field has become since you first broke into it? [00:09:41] Where do you see the field headed in the next two to five years? [00:11:20] What do you think would be the biggest positive impact that Data science will have on society in the next two to five years? [00:12:36] What do you think would be the scariest application of machine learning and data science in the next two to five years? [00:13:17] As practitioners of machine learning, what do you think would be some of our biggest concerns when we're out there doing our work? [00:16:01] What is Churn? Is that what we do we make butter. [00:17:27] So why is churn so hard to fight? [00:21:48] The importance of metrics in our battle against churn [00:24:01] How do we go from raw event data to metrics? [00:24:45] How do cohorts help us analyze, predict, and understand churn? [00:27:22] What are ratio metrics and why are they so powerful? [00:33:09] Why are outliers so problematic to deal with? model and get information from them, but without them ruining your numbers. [00:34:57] What are some common mistakes that you've seen Data scientists make when it comes to dealing with outliers? [00:39:14] How to be more thoughtful when it comes to feature engineering? [00:42:31] Debunking the common misconception that the choice of algorithm is the most important thing that contributes to model performance. [00:43:56] Your features don’t need to be the most creative [00:45:28] Your job isn’t over once you deploy the model [00:49:05] What are some things that we need to monitor and track - the context of churn - to make sure that our model is doing what it should be, that is performing as we've designed it? [00:50:26] How COVID is messing up everyone’s churn models [00:53:14] Is data science an art or science? [00:55:24] What are some soft skills that Data scientists are missing that are really going to help them take their careers to the next level? [00:56:51] How could a data scientist develop their business acumen and their product sense [00:57:44] What to do with these crazy job descriptions [00:59:27] What’s the one thing you want people to learn from your story? [01:00:39] The lightning round Special Guest: Carl Gold, Phd.
Brenden is passionate about helping others achieve rocket level success. He lives by the philosophy that when you care about serving others and aim to add value to people’s lives, you’ll be able to overcome any fear or obstacle in your path. This philosophy has led to him coaching purpose driven entrepreneurs on how to master their message and share their ideas with the world. FIND BRENDEN ONLINE LinkedIn :https://www.linkedin.com/in/brendenkumarasamy Website: https://www.mastertalk.ca/ YouTube: https://www.youtube.com/channel/UCBYFP4mZLQovr7W6Si6sueA Twitter: https://twitter.com/masteryourtalks Instagram: https://www.instagram.com/masteryourtalk/ QUOTES [00:05:00] "Everyone seems to ask themselves what they're passionate about. And I think that is a stupid question. And let me explain why." [00:07:04] "There are a lot of people who know how to crunch numbers but don't know how to explain them back to people in a way that can be philosophically transformative in people's lives." [00:08:14] "Public speaking is a skill that anyone can master, but very few people do because it's the hardest skill to hold yourself accountable to." [00:12:33] "The secret is there is no secret in the sense that if you think you're able to engage your audience from the first time you present something, you're wrong. " [00:18:29] "But if you talk to your audience and just ask yourself the simple question, what are you trying to achieve here? You're trying to help them take a first step. You're trying to get the introverted data scientist to say, hey, you have an idea to share." [00:21:27] "We're taught to believe that public speaking is a chore. Public speaking is a responsibility and obligation. " [00:32:43] "If you want to stand out in general, you need to be able to tell a story with that data. And by story, I don't mean storytelling going in all this persona's stuff. I mean structuring your ideas in a way that makes sense to a fifth grader who doesn't understand Data science." SHOW NOTES [00:01:35] Introduction for our guest today [00:02:47] How Brenden paved his own lane [00:04:36] How Brenden decided that his mission is to help people be better public speakers [00:08:04] The “Public Speaking Why” [00:09:49] How would the world change if you were an exceptional communicator? [00:10:56] What's the difference between just talking and speaking? [00:12:16] How do we present information in a way that will get our audience excited and get them excited to hear us share our ideas with them and with the world? [00:15:41] How do the best speakers in the world design presentations for maximum effect? [00:19:18] Change your mindset about public speaking [00:23:18] An exercise for improving your public speaking (I give Brenden a random word and he makes a speech on the spot). [00:27:05] How important is writing when preparing for speaking? [00:28:53] How can we become better storytellers? [00:31:15] How can we identify personas in our audience [00:33:57] How to communicate with executives [00:37:06] How to make the most of networking events [00:39:55] Tips to start becoming a better presenter, today! [00:41:28] How to move from individual contributor to leadership [00:43:58] Charity water [00:48:35] What's the one thing you want people to learn from your story? [00:50:52] The lightning round Special Guest: Brenden Kumarasamy.
Excellent questions this week! We do a portfolio project review, technical feedback for a project, talk about what the difference is between a data science manager and a data science project manager. The participants turn the tables on me in this one and interview me about my process, routines, and how I find people for the podcast. Join Data Science Dream Job for 70% off: http://dsdj.co/artists70 Watch the episode on YouTube here: https://youtu.be/1TNjun5t5O8 We were voted one of the top ten data science podcasts by FeedSpot - check it out here: https://blog.feedspot.com/datasciencepodcasts/ I was on the Human Prosperity podcast, check it out here: https://www.youtube.com/watch?v=RbD3aV2TfKk Check it out and don't forget to register for future office hours: http://bit.ly/adsoh
Dr. Prewitt is a thought leader in innovation, education, and entrepreneurship. In addition to working as an engineer and researcher with several Fortune 500 companies and universities before starting his business, he’s also an active researcher, author, and speaker in the areas of innovation, education, and entrepreneurship. He’s given talks across the country on topics ranging from student success in STEM to how to leverage technology for business success. He’s also co-author of a book for students interested in pursuing careers in technology titled STEM Navigators. FIND ANDERSON ONLINE WEBSITE: https://www.andersondprewitt.com/ LINKEDIN: https://www.linkedin.com/in/dradprewitt/ TWITTER: https://twitter.com/prewittsolution FACEBOOK: https://www.facebook.com/DrADPrewitt QUOTES [00:12:03] "Data can also be used to harm if it's not done the correct way...I think a very good example is something like we look at things like systemic inequalities, systemic racism, systemic sexism, all of it. We spend a lot of time talking about the sexism, the racism, the inequality. We don't spend as much time talking about the system and really about race. " [00:15:51] "I try to talk about A.I. in terms of raising a child or maybe whatever else... if you train that child up or that baby up and you teach them a wide range of things, they get experiences and you yourself have enough knowledge and actually take the time to learn the right things, teach them, then that child has a better chance of growing up and doing the right things." [00:22:17] "I think that even some basic understanding of information can be misused for how one wrong line of code or not having a full dataset can affect people in real terms in real time" [00:30:27] "If you don't know that there are multiple paths to get to something, you're only going to go down the road that you know" SHOW NOTES [00:02:05] Introduction for our guest [00:03:25] How Dr. Prewitt got into data science [00:07:56] Challenges on the path to getting a PhD [00:10:43] Where is data science headed in the next two to five years? [00:15:38] What can we do as practitioners of Data science machine learning to make sure that the work that we're doing isn't perpetuating negative biases? [00:18:43] Think holistically about what you are building [00:20:36] How can we educate ourselves on ethics? Where do we turn to for guidance on that to make sure that the work that we are doing is ethical? [00:23:35] How to take ownership of your self-education [00:26:17] Don’t torture the data until it confesses [00:27:47] STEM Navigators [00:33:02] How do systems work? [00:38:15] How to use AI for good [00:41:09] Advice to students who are interested in studying science, technology, engineering or math [00:44:13] Going back to your book, STEM Navigator's talk about curiosity and asking why not? Do you feel that was a common thread or formula to success for the navigator's that you highlighted in the book? [00:45:42] Battling imposter syndrome [00:48:24] The cookie jar [00:51:26] What can the STEM community do to foster the inclusion of people of color, especially black Americans in particular in our field? [00:54:46] What's the one thing you want people to learn from your story? [00:55:38] The lightning round Special Guest: Anderson Prewitt, PhD.
Andrew is an American statistician, professor of statistics and political science, and director of the Applied Statistics Center at Columbia University. He frequently writes about Bayesian statistics, displaying data, and interesting trends in social science. He’s also well known for writing posts sharing his thoughts on best statistical practices in the sciences, with a frequent emphasis on what he sees as the absurd and unscientific. FIND ANDREW ONLINE Website: https://statmodeling.stat.columbia.edu/ Twitter: https://twitter.com/StatModeling QUOTES [00:04:16] "We've already passed peak statistics..." [00:05:13] "One thing that we sometimes like to say is that big data need big model because big data are available data. They're not designed experiments, they're not random samples. Often big data means these are measurements. " [00:22:05] "If you design an experiment, you want to know what you're going to do later. So most obviously, you want your sample size to be large enough so that given the effect size that you expect to see, you'll get a strong enough signal that you can make a strong statement." [00:31:00] "The alternative to good philosophy is not no philosophy, it's bad philosophy. " SHOW NOTES [00:03:12] How Dr. Gelman got interested in statistics [00:04:09] How much more hyped has statistical and machine learning become since you first broke into the field? [00:04:44] Where do you see the field of statistical machine learning headed in the next two to five years? [00:06:12] What do you think the biggest positive impact machine learning will have in society in the next two to five years? [00:07:24] What do you think would be some of our biggest concerns in the future? [00:09:07] The thee parts of Bayesian inference [00:12:05] What's the main difference between the frequentist and the Bayesian? [00:13:02] What is a workflow? [00:16:21] Iteratively building models [00:17:50] How does the Bayesian workflow differ from the frequent workflow? [00:18:32] Why is it that what makes this statistical method effective is not what it does with the data, but what data it uses? [00:20:48] Why do Bayesians then tend to be a little bit more skeptical in their thought processes? [00:21:47] Your method of evaluation can be inspired by the model or the model can be inspired by your method of evaluation [00:24:38] What is the usual story when it comes to statistics? And why don't you like it? [00:30:16] Why should statisticians and data scientist care about philosophy? [00:35:04] How can we solve all of our statistics problems using P values? [00:36:14] Is there a difference in interpretations for P-Values between Bayesian and frequentist. [00:36:54] Do you feel like the P value is a difficult concept for a lot of people to understand? And if so, why do you think it's a bit challenging? [00:38:22] Why the least important part of data science is statistics. [00:40:09] Why is it that Americans vote the way they do? [00:42:40] What's the one thing you want people to learn from your story? [00:44:48] The lightning round Special Guest: Andrew Gelman, PhD.
This office hours was jam packed with some amazing insights from data scientists at all levels! Carlos Mercado stops by and brings some friends with him! We help a community member with their workflow for a Kaggle project and discuss some best practices for working on a project. We also talk about how a data scientists needs to have a duality mindset - they're the bridge between technical engineers and the research scientists in their organizations. We also get to hear what it's like being a data scientist in a consulting organizations, and the challenges of working with clients who don't know what they want. Some awesome book recommendations in this episode as well! We were ranked one of the top data science podcasts by FeedSpot! Check it out here: https://blog.feedspot.com/datasciencepodcasts/ You can checkout the video on YouTube here: https://www.youtube.com/watch?v=dtrGkaqniyQ Get 70% off of Data Science Dream Job's registration fee: dsdj.co/artists70 Register for future office hours: bit.ly/adsoh Join Data Science Dream Job for 70% off: http://dsdj.co/artists70 Special Guest: Carlos Mercado.
Anderson Silver is a CPA who landed his dream job earning a six-figure salary, complete with high profile notoriety and accolade. Looking for a guide to life, he turned to philosophy and for the last five years he’s been practicing the philosophy of Stoicism, and it’s changed his life completely. QUOTES [00:11:40] "The more the island of my knowledge grows, the more the shore of my ignorance grows." [00:17:06] "Let's stop pretending that this fake structure we have actually means something. Which is ironic coming from the Stoics because, you know, some of the most famous Stoics were the richest man in all the lands. " [00:25:42] "Your intention, your decision for the action is in your control. But as soon as you start trying to do it, it's already out of your control." [00:32:04] "There's no one right answer to what the purpose of life is. We all have our own unique purpose for life. And but the thing is, we never take the time to identify this, right?" WHAT YOU'LL LEARN [00:07:26] The difference between stoic and Stoicism [00:09:40] Socrates, wisdom, and virtue [00:21:31] The key disciplines of Stoicism [00:26:28] Premeditation of adversity [00:56:03] The three reasons Anderson practices Stoicism FIND ANDERSON ONLINE Twitter: https://twitter.com/yourmanual Patreon: https://www.patreon.com/AndersonSilver Podcast: https://anchor.fm/AndersonSilver SHOW NOTES [00:01:37] Guest introduction [00:02:55] The journey to now [00:03:53] The path to philosophy [00:05:14] The search for a philosophy of life [00:07:26] The difference between stoic and Stoicism [00:09:40] Socrates, wisdom, and virtue [00:14:10] The difference between cynicism and Cynicism [00:16:35] Living in accordance with nature [00:19:16] The nature of the 21st century [00:21:31] The key disciplines of Stoicism [00:26:28] Premeditation of adversity [00:30:12] How can we make sure that we're not being busy for the wrong reasons? [00:33:18] Dealing with selfish impulses and distractions [00:36:34] The Stoic practice of journaling [00:37:44] Stoicism and job interviews [00:40:55] Stoicism and the art of being a sports fan [00:42:29] Owning up to insecurities at work [00:45:07] How to handle feeling overwhelmed at work [00:46:56] Love your destiny [00:48:49] What do to do if your boss is an asshole [00:50:10] How not to be angry at your coworkers [00:52:33] Throw away your books [00:56:03] The three reasons Anderson practices Stoicism [00:57:08] The Stoic parent [01:00:05] What do the Stoics have to say about worrying about what other people think about you? [01:02:27] What's the one thing you want people to learn from your story? [01:03:54] The lightning round Special Guest: Anderson Silver.
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