Super Data Science: ML & AI Podcast with Jon Krohn

Dr. Brett Tully joins us on the podcast to discuss his work as Director of AI Output Systems at Nearmap and his previous research in biomedical topics and nuclear fusion. In this episode you will learn: What is Nearmap? [5:22] What is a Director of AI Output Systems? [7:51] A case study [20:35] MLOps at Nearmap [26:37] Brett’s day-to-day and what he looks for in hires [40:19] Brett’s academic and...

Jon discusses one helpful framework when it comes to problem-solving and how data scientists are uniquely positioned to employ this technique. Additional materials: www.superdatascience.com/532

Jeroen Janssens joins on the podcast to discuss his book on utilizing the command line for data science and the importance of polyglot data science work. In this episode you will learn: The genesis of Jeroen’s book [3:24] Data Science at the Command Line [8:55] Creating your own command line tools [22:07] Polyglot data scientist [24:29] Data Science Workshops [27:01] Jeroen’s PhD research [30:38]...

Jon details his top ten AI thought leaders hoping that his suggestions prove valuable to you in your data science journey. Additional materials: www.superdatascience.com/530

Dave Niewinski joins us to discuss his prolific work in robotics both as a consultant and a popular YouTuber. In this episode you will learn: Dave’s Armoury [4:44] Robotic cornhole tournament [12:33] Dave’s many robots [14:25] Dave’s idea process [28:51] Future robots [31:43] Dave’s consulting business [33:27] Tools Dave likes to use [37:05] How did Dave get started in this line of work? [38:50] D...

Jon explores his personal anxieties as a content creator to encourage fellow creators to keep sharing their knowledge. Additional materials: www.superdatascience.com/528

Peter Bailis joins the podcast to discuss the work of his company that solves complex commercial problems through automated data analysis. In this episode you will learn: Meaning of the name Sisu [3:08] What Sisu does [4:45] Sisu and the data science stack [17:00] Going from academia to startups [22:37] What Sisu looks for when hiring [28:57] Peter’s favorite tools [32:40] Peter’s academic researc...

I finish up our three-part series on the results of the O’Reilly Survey, looking at the highest-paying data frameworks. Additional materials: www.superdatascience.com/526

Karen Jean-Francois joins us to discuss how she wants to empower her team members and a wider audience of data scientists battling imposter syndrome. In this episode you will learn: Karen’s background as a hurdler [4:42] Women in Data Podcast [10:32] Cardlytics [19:04] Karen’s background and current career [22:55] Karen’s favorite tools [31:29] Karen’s balance of fitness and work [34:45] The bigge...

In this episode, I go over the highest-paying data tools based on the O’Reilly survey. Additional materials: www.superdatascience.com/524

Wes McKinney joins us to discuss the history and philosophy of pandas and Apache Arrow as well as his continued work in open source tools. In this episode you will learn: History of pandas [7:29] The trends of R and Python [23:33] Python for Data Analysis [25:58] pandas updates and community [30:10] Apache Arrow [41:50] Voltron Data [55:10] Origin of Wes’s project names [1:08:14] Wes’s favorite to...

I provide you with some quick definitions of data tools vs data platforms to prep us for deep dives in future episodes. Additional materials: www.superdatascience.com/522

Khuyen Tran joins us to discuss her work as a prolific technical writer and undergraduate data science student. In this episode you will learn: Khuyen’s online writing [4:00] Book writing [8:50] How you can increase your engagement [13:49] Khuyen’s work with Towards Data Science and NVIDIA [19:01] Ocelot Consulting [24:08] Khuyen’s undergrad work [32:12] Audience questions [47:00] Additional mater...

I take a look at the results of O’Reilly’s survey on salaries for data scientists in 2021. Additional materials: www.superdatascience.com/520

James Hodson joins us to discuss his philosophy and work at A.I. For Good and how they aim to promote sustainability and A.I. use for social issues. In this episode you will learn: AI for Good [5:17] Founding of AI for Good [8:50] Case studies [14:58] How you can get involved [46:29] Skills James looks for in hires [50:39] Additional materials: www.superdatascience.com/519

This week, I provide a short but important bit of advice on failure. Additional materials: www.superdatascience.com/518

Sadie St. Lawrence talks in-depth about her extensive work as a data science educator through both online and collegiate courses as well as her organization for diversifying data science careers. In this episode you will learn: Sadie’s education work in SQL [4:13] The popularity of Sadie’s course [13:32] Sadie’s forthcoming machine learning certificate course [16:29] Women in Data [25:32] Sadie’s...

In this episode, I finish up my saga into the effects of caffeine on productivity. Additional materials: www.superdatascience.com/516

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 f...