Superdatascience

Chrys Wu joins us to discuss her community organizations, her tips, and her recommended resources for building data science communities for impact. In this episode you will learn: The world of K-Pop [ 4:07] Chrys’s talk at the R Conference [8:56] Write/Speak/Code [14:05] Hacks/Hackers [21:58] Tips on developing data communities [27:22] Additional materials: www.superdatascience.com/515

In this episode, I dive into the nuts and bolts of data on my experiment into caffeine and productivity. Additional materials: www.superdatascience.com/514

Denis Rothman joins us to discuss his writing work in natural language processing, explainable AI, and more! In this episode you will learn: What are transformers and their applications? [7:54] Denis’s book on explainable AI [25:08] AI by Example [35:53] LinkedIn audience questions [42:00] Additional materials: www.superdatascience.com/513

I dive into a personal experiment to test my productivity relative to my coffee intake and if caffeine is actually hurting my productivity. Additional materials: www.superdatascience.com/512

Drew Conway joins us on the first live podcast to discuss his work in private investing and how data science figures into and improves his work. In this episode you will learn: The R Conference and NYHackR [6:33] Machine Learning for Hackers [20:17] Two Sigma and Drew’s work [28:27] Drew’s team structure at Two Sigma [35:12] Audience Q&A [46:27] Additional materials: www.superdatascience.com/511

In this episode, I dive into the world of reinforcement learning and deep reinforcement learning and the benefits of both. Additional materials: www.superdatascience.com/510

Parinaz Sobhani joins us to discuss the cutting-edge work of Georgian, a collaborative company that helps start-ups implement and scale machine learning and AI. In this episode you will learn: Parinaz’s work at Georgian [5:35] Use cases of Georgian’s work [14:35] Tools and approaches Parinaz uses [32:27] Environmental concerns of machine learning [42:52] Hiring at Georgian and what Parinaz looks for [48:18] How did Parinaz become interested in this? [56:19] Fairness in AI [1:09:01] Additional materials: www.superdatascience.com/509

In this episode, I discuss an interesting bit of my grandmother’s view about the process of working and going through life. Additional materials: www.superdatascience.com/508

Rob Trangucci joins us to discuss his work and study in Bayesian statistics and how he applies it to real-world problems. In this episode you will learn: Getting Rob on the show [8:12] Stan [9:34] Gradients [18:15] What is Bayesian statistics? [23:05] Multi-modal deep learning [45:20] Stan package [53:46] Applications of Bayesian stats [1:09:47] The day-to-day of a PhD in stats [1:21:56] What does the future hold? [1:42:37] Additional materials: www.superdatascience.com/507

In this episode, I continue with last week’s theme and discuss the differences between supervised and unsupervised learning. Additional materials: www.superdatascience.com/506

Hadelin de Ponteves joins us to discuss his latest educational work and how his skills as a data science educator helped him start his career in acting. In this episode you will learn: What has Hadelin been up to? [4:27] Hadelin’s cinema career and data science crossover [16:02] Sleep for productivity [27:27] How did Hadelin decide to undertake this? [32:26] Bollywood vs Hollywood [37:26] Additional materials: www.superdatascience.com/505

In this episode, I give a quick introduction to subcategories of supervised learning problems. Additional materials: www.superdatascience.com/504

Pieter Abbeel joins us to discuss his work as an academic and entrepreneur in the field of AI robotics and what the future of the industry holds. In this episode you will learn: How does Pieter do it all? [5:45] Pieter’s exciting areas of research [12:30] Research application at Covariant [32:27] Getting into AI robotics [42:18] Traits of good AI robotics apprentices [49:38] Valuable skills [56:40] What Pieter hopes to look back on [1:04:30] LinkedIn Q&A [1:06:51] Additional materials: www.superdatascience.com/503

In this episode, I explore a common issue plaguing people across fields: imposter syndrome. Additional materials: www.superdatascience.com/502

Jared Lander joins us to discuss his work as an R meetup organizer, the upcoming virtual R Conference, and his work as a consultant for a variety of companies from metal workers to professional football teams. In this episode you will learn: Jared’s R meetups and our professional history [3:27] NYHackR [6:42] The R Conference [13:25] R for Everyone [18:55] Lander Analytics [22:10] Job openings at Lander Analytics [25:04] R vs. Python [29:15] The importance of pizza in Jared’s life [32:19] Additional materials: www.superdatascience.com/501

In this very special episode, we delve into a live yoga Nidra practice with Jes Allen and go over how you can open up to consciousness through yoga practice. In this episode you will learn: [3:40] What Yoga means [10:00] Jes’s current work as a yoga practitioner [22:31] How to find Jes online [27:09] The Yoga Nidra practice [54:50] Coming out of the practice Additional materials: www.superdatascience.com/500

Barr Moses joins us to discuss the importance of data reliability for pipelines and how companies can achieve data mesh. In this episode you will learn: Data meshes [4:25] Self-serve data reliability [15:36] How Monte Carlo helps data up time [21:13] How to build an effective data science team [26:50] LinkedIn Q&A [31:50] Additional materials: www.superdatascience.com/499

In this episode, I dive into a reoccurring pattern I’ve noticed where beginners, myself included, think they’re more skilled and experienced than they really are. Additional materials: www.superdatascience.com/498

Benjamin Todd joins us to discuss his work helping professionals maximize their career capital, the top skills to learn across professions, and more. In this episode you will learn: How Benjamin helped me become a data scientist [6:56] How did 80,000 Hours come about? [9:39] The impact of 80,000 Hours [14:46] Funding [17:23] Where does the name come from? [23:32] What kind of advice does Benjamin give to people? [25:21] How data scientists can make an impact [42:04] How can someone strategize about their career? [1:02:53] Top skills that everyone should learn [1:05:49] Additional materials: www.superdatascience.com/497

In this episode, you’ll enjoy a fictional narrative I’ve titled “2040: A Brain-Computer Interface Story”. Additional materials: www.superdatascience.com/496