The Artists of Data Science

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 roundSpecial 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/data_science_podcasts/ 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/artists70Special 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 roundSpecial Guest: Anderson Silver.

Jacqueline Nolis, a principal data scientist at Brightloom, and Emily Robinson, a senior data scientist at Warby Parker, dive into the world of data science careers. They discuss the three types of data scientists and how to transform business problems into data challenges. The duo also tackles effective analysis strategies, transitioning models into production, and the importance of clear communication with stakeholders. Their journey co-authoring a data science book highlights collaboration, inclusivity, and the significance of foundational data engineering.

Carlos swings by the office hours again and we have an excellent discussion with a community member on why it's important to not compare yourself to what other data scientists know and don't know. This is a great session to listen to for anyone who may be feeling a bit of imposter syndrome, or maybe feeling like that don't have value to contribute. We also talk about the perils of working out of a notebook, and how to move beyond them. Checkout the recording on YouTube: https://www.youtube.com/watch?v=m_dxtAIKbZc Check out the live session I did with Kate Strachnyi: https://www.youtube.com/watch?v=soyWLCsAEuY The Artists of Data Science was named #8 on the Top 15 Data Science podcasts by FeedSpot! https://blog.feedspot.com/data_science_podcasts/ Some items we talked about in this episode: [16:42] Carlos Mercado tells Haseeb about a quote has made his life in meetings of 10 people much easier: "Sometimes the most basic obvious thoughts are just coincidentally not in anyone else's head at the time. 'What's obvious to you is amazing to others'" [16:43] Carlos Mercado : "Also most data science problems are shockingly not complex" [16:45] Harpreet Sahota talks about an episode with Brandon Quach that addresses the question that Haseeb has. Check it out here: https://theartistsofdatascience.fireside.fm/brandon-quach [16:59] Community member Haseeb shares an awesome video he made on the perils of working in a notebook: https://youtu.be/kBnCOOrSh1U [17:11] I talk about the future of The Artists of Data Science and what my vision for it is [17:12] Carlos shares his ideas for a couple of cool things that The Artists of Data Science could do. [17:22] Haseeb shares a data science meet-up group Join Data Science Dream Job for 70% off: http://dsdj.co/artists70 Check it out and don't forget to register for future office hours: http://bit.ly/adsohSpecial Guest: Carlos Mercado.

Ashley's a Data Analyst collaborating with administrators and medical professionals to develop impactful analysis utilizing data mining, visualizations, and modeling to drive business solutions. She’s a passionate advocate for educating women regarding data career opportunities and spreading awareness about the advancement of women in the tech industry. And she's a Forbes Under 30 Scholar! WHAT YOU'LL LEARN [00:05:32] The importance of cultivating the right mindset [00:17:04] Privacy, biometrics, and data [00:25:03] How to become a Forbes under-30 scholar [00:27:09] The unique experiences of a health care data analyst [00:30:54] Bridinging the patient satisfaction gap with data [00:43:57] Emotional intelligence in data science FIND ASHLEY ONLINE LinkedIn: https://www.linkedin.com/in/ashleym-scott/ Instagram: https://www.instagram.com/datagirlash/ Twitter: https://twitter.com/datagirlash SHOW NOTES [00:01:35] Introduction for our guest today [00:02:49] The journey into analytics [00:07:50] The data hype cycle [00:11:09] How do you see data analytics impacting the health care industry in the next two to five years? [00:17:04] Privacy, biometrics, and data [00:21:24] What do you think will separate the great Data scientists from the merely good ones? [00:25:03] How to become a Forbes under-30 scholar [00:27:09] The unique experiences of a health care data analyst [00:30:54] How is Data bridging the gap between medical education and patient satisfaction? [00:32:51] Health care data analyst project ideas [00:39:08] How to decide your data science career path [00:43:57] Emotional intelligence in data science [00:48:01] What are some common mistakes that you see people make when visualizing their data? [00:50:37] Communicating with non-technical audience [00:54:17] Openly communicate with your teammates [00:56:26] Being a woman in data science [00:59:12] The Women in Data Science organization [01:05:26] Fostering inclusion of women in data science [01:07:45] What's the one thing you want people to learn from your story? [01:09:00] The lightning roundSpecial Guest: Ashley M. Scott.

Giuseppe Bonaccorso is an experienced and goal-oriented leader with wide expertise in the management of Artificial Intelligence, Machine Learning, Deep Learning, and Data Science. His experience spans projects for a wide variety of industries including: healthcare, B2C and Military industries, and Fortune 500 firms. His main interests include machine/deep learning, data science strategy, and digital innovation in the healthcare industry. You may recognize him from the many best-selling machine learning books he’s published including: Python: Advanced Guide to Artificial Intelligence, Fundamentals of Machine Learning with scikit-learn, and Hands-On Unsupervised Learning with Python. WHAT YOU'LL LEARN [00:13:01] The need for creating a culture of data science [00:16:08] Why you need to be more than a nerd [00:27:06] Heuristics for scaling data [00:35:50] How to cross-validate [00:43:53] Feature engineering techniques [00:46:50] A lesson on tuning hyperparameters [00:51:33] A lesson on using regularization [00:58:01] What to do after model deployment QUOTES: [00:10:29] "Data science is not something that can be learned in a week or even in a month. It's a real topic with a lot of theory behind. And it's very important for the practitioners to have clear ideas about what they do." [00:22:45] "Another very important thing when defining a model is that our goal is not necessarily to describe what we already know, but to make predictions. So our model must become a sort of container of future possibilities. " [01:06:14] "Data science is a science for sure. There is mathematics behind and we never we should never forget this. But I consider also mathematics and mix of science and art." [01:09:48] "The only way you can really expand yourself is to be curious, to learn the new processes, to learn how other people work, to talk to other people, to understand how your business work." FIND GIUSEPPTE ONLINE: Website: https://www.bonaccorso.eu/ LinkedIn: https://www.linkedin.com/in/giuseppebonaccorso/ Twitter: https://twitter.com/GiuseppeB SHOW NOTES: [00:01:44] Introduction for our guest [00:03:06] How Giuseppe got into data science [00:04:37] The hype around data science [00:06:10] Machine learning in the future [00:07:33] The biggest positive impact data science will have in the near future [00:10:13] How to minimize the negative impacts of data science [00:13:39] Healthy vs unhealthy data science culture [00:17:45] Good vs great data scientists [00:21:50] What's artists I would love to hear from you. [00:22:33] What is a model and why do we build them in the first place? [00:27:06] Heuristics for scaling data [00:35:50] With so many methods of cross-validation out there, how can we know which one to utilize for any given scenario? [00:43:43] How we can be more thoughtful with our feature engineering feature? [00:46:50] Tips on tuning hyperparameters [00:51:33] A lesson on using regularization [00:58:01] What to do after deployment [01:01:24] The data generating process [01:04:00] Keywords you need to search to learn more about different parts of the machine learning pipeline [01:06:01] Do you consider Data science and machine learning to be an art or purely a hard science? [01:07:21] Creativity and curiosity [01:10:38] How could Data scientists develop their business acumen and cultivate a product sense? [01:13:50] Advice for people breaking into the field [01:17:19] What’s the one thing you want people to learn from your story? [01:19:08] The lightning roundSpecial Guest: Giuseppe Bonaccorso.

The recording from open office hours! Carlos Mercado swings by the show and he talks about the work he does with the government, talks about health care data scientists, and discusses some project ideas. We also have a Q&A session with communit members, talk about blockchain, and more! Check it out and don't forget to register for future office hours: http://bit.ly/adsoh Checkout the recording on YouTube: https://bit.ly/3jc2qcf Join Data Science Dream Job for 70% off: http://dsdj.co/artists70Special Guest: Carlos Mercado.

Dr. Alex Pang studies people, technologies, and the worlds they make. Since 2000 he's worked as a technology forecaster and futurist, helping companies understand new technologies and global trends, and their strategic and business implications. QUOTES "The challenge is figuring out how it's going to play out in different industries or different parts of the world, thinking about how we can control and shape those technologies and their users so that they give us more flexibility, more autonomy, more freedom, as opposed to just eliminating our jobs or doing other bad things." ] [00:09:11] "I think that the this is we live in a world that doesn't take work seriously, but we also live in a world that provides us with all the tools necessary to figure out how to harness rest and bring it back on our lives and use it as something that makes our lives better and makes our work better. " [00:16:53] "One of the other things, though, is that Ericsson found was that not only the top performers practiced differently, they also rested differently. They actually slept more than average performers..." [00:19:52] "And why that's important is that our creative minds seem to do better when - with these routines. Stephen King has this line about how the muse will descend if it knows that you're working." [00:34:18] "Basically, intensive periods of focused work be periods of long semi distracted work. Knowledge work is a little bit more like high intensity interval training than like running a marathon. It turns out that intense-ivity turns turns out to be a better route to higher performance and better results than the long, long grind. [00:50:41]" [00:50:16] FIND ALEX ONLINE: LinkedIn: https://www.linkedin.com/in/askpang/ Twitter: https://twitter.com/askpang SHOW NOTES [00:02:16] Introduction for our guest [00:03:16] How Alex got so interested in the role of rest in creative lives [00:06:36] Where do you see technology headed in the next two to five years? [00:09:32] Society’s biggest concern with technology in the next 2-5 years. [00:12:03] What can we do now and perhaps going into the future to mitigate our distraction from technology [00:14:41] What is rest and what's the problem with it? [00:17:13] The problem with the “hustle culture” [00:18:54] Deliberate practice, deliberate rest [00:20:42] Why is it that rest is important for those of us who don't use our bodies or tactile kind of appendages, we use our brains? [00:23:02] The default mode network of the brain [00:27:51] How can we convince our boss that all we need is a solid four hours? [00:29:11] What are some horrible ways that people are resting and we should probably stop resting that way? [00:33:42] How does having a daily routine help us be more creative? How does that help us be more productive? [00:36:44] I talk about my struggles with my morning routine [00:37:50] What is the design thinking framework? [00:42:54] How can this framework then help us work better, smarter and less? [00:49:02] How to work more effectively as a knowledge worker [00:50:42] Flex time is not really that great [00:52:44] What's the one thing you want people to learn from your story. [00:53:36] Lightning round. What is your favorite way to rest? [00:53:46] If you could put up a billboard anywhere in the world, what would it say and why? [00:54:00] What something you believe that other people think is crazy. [00:54:50] What would you say is the most bizarre aspect or quality of the human mind that you've come across? [00:56:04] An interesting topic you should study [00:56:25] What's the number one book you'd recommend our audience read and your most impactful takeaway from it? [00:57:12] If you could somehow get a magic telephone that allows you to to contact 20 year old Alex, what would you tell him? [00:58:20] What does creativity have to do with being a good scientist? [00:59:34] What song do you have on repeat right now? [01:01:02] What's the best advice you've ever received? [01:01:48] Where to find Alex onlineSpecial Guest: Alex Pang, PhD.

On this episode of The Artists of Data Science, we get a chance to hear from Gilbert Eijkelenboom, an author and behavioral economist that is passionate about bridging the gap between analytical thinkers and emotional intelligence. His passion for psychology and numbers has led him to understand the need for analytical minds to become better at communication with people. He gives insight into how your brain works, his methods for getting great feedback, and the importance of emotional intelligence. Gilbert talks about his background as a poker player, and how human behavior impacts the success that is possible in data science and beyond. This episode brings an interesting and very important perspective into soft skills and actionable tips to implement into your daily workstream. WHAT YOU'LL LEARN [12:14] How your brain works and influences daily decisions [18:58] The importance of saying no [21:38] What is emotional intelligence and how it impacts your personal and professional life [37:26] How to identify your bright spot [44:21] The three step process to change your algorithms [46:58] Gilbert’s take on intrapreneurship QUOTES [21:38] “...to become a really good data scientist, you need to understand the business problem...and without emotional intelligence, it's going to be very difficult.” [24:53] “...if you don't try it yourself and fail and learn and experiment, then you're never going to be good…” [53:12] “every day you make small decisions that all combine to really big growth” FIND GILBERT ONLINE: Website: https://www.mindspeaking.com/ Quora: https://www.quora.com/profile/Gilbert-Eijkelenboom LinkedIn: https://www.linkedin.com/in/eijkelenboom/ SHOW NOTES [00:01:35] Introduction for our guest [00:02:45] How Gilbert went from poker pro to data dude [00:04:48] Where do you see the field of analytics and data science headed in the next two to five years? [00:06:09] The difference between good and great data scientists [00:06:55] Data science and behavioral economics [00:08:44] How we can see our brain as a set of algorithms with an input process and output? [00:12:01] The two systems in the brain [00:15:40] How to cope with rejection in our job search [00:18:36] The importance of saying no [00:21:03] What is emotional intelligence [00:21:31] The importance of emotional intelligence in our personal and professional lives [00:23:52] Why emotional intelligence is so important and the challenges of acquiring this skill [00:26:22] Tips on what we could do to start developing better emotional intelligence [00:28:16] How to ask for feedback [00:33:07] We talk about our shared love of Steven Pressfield [00:35:43] Emotional intelligence in the virtual world. [00:37:14] How we can identify our "bright spots" [00:39:00] How to cultivate better self-awareness [00:41:15] How we create a better awareness of the algorithms in our head [00:44:02] A three-step process for changing the negative algorithms in our heads [00:46:34] What it means to be an intrapreneur [00:49:24] What's the one thing you want people to learn from your story? [00:50:54] Why Gilbert wants to impact 100,000 people [00:51:57] The Lightning RoundSpecial Guest: Gilbert Eijkelenboom.