Superdatascience

Prolific data science entrepreneur and Y Combinator alum Austin Ogilvie (Laika, Yhat) joins Jon Krohn for a revealing look into his journey of starting, growing, and selling a data science startup. From liberal arts graduate to twice successful technical founder, take a seat and learn from the best. In this episode you will learn: The story behind the naming of Yhat and its early beginnings [5:10] Austin and Yhat's experience at Y Combinator [19:00] The benefits of being a technical founder [25:00] From arts degree graduate to successful tech entrepreneur [27:00] Austin's latest venture, Laika [39:30] The tools that Austin uses day-to-day [47:30] Unity gaming environment [49:58] What makes a great data scientist [56:23] Additional materials: www.superdatascience.com/535

Jon sends a holiday greeting to all listeners. Additional materials: www.superdatascience.com/534

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 research history [53:30] Brett’s work in nuclear fusion and predictions for the technology [1:04:48] The tools Brett used in his research [1:26:34] ProCan project [1:34:27] Brett’s prediction for future AI applications [1:48:30] Additional materials: www.superdatascience.com/533

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] Additional materials: www.superdatascience.com/531

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] Dave’s advice to people who want to get into robotics [41:18] What is Dave excited about in the future? [45:38] Additional materials: www.superdatascience.com/529

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 research [45:02] Additional materials: www.superdatascience.com/527

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 biggest challenge of Karen’s career [47:09] Advancement in data [54:13] What is Karen most excited about? [59:40] Additional materials: www.superdatascience.com/525

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 tools [1:09:46] Audience Q&A [1:15:34] Additional materials: www.superdatascience.com/523

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 materials: www.superdatascience.com/521

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 non-technical background [36:17] NFTs and VR [46:41] Additional materials: www.superdatascience.com/517

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