Super Data Science: ML & AI Podcast with Jon Krohn

In this episode, superstar data science YouTuber Tina Huang joins us to discuss what it's like to work at one of the world's largest tech companies, her strategies for efficient learning, and how best to prepare for a career in data science from scratch.In this episode you will learn: The key areas to focus on when getting started in data science [6:01] Tina’s five steps to consistently doing anything [11:55] Tina's day-to-day life as a data scientist at one of the world’s largest tech companies [20:02] How Tina's computer science background helps her work [26:20] Traditional banking culture vs big tech [32:12] How Tina's background in pharmacology impacts her work in data science [36:15] The software languages that Tina uses daily in her work [45:30] How Tina’s SQL course practically prepares you for data science interviews [47:24] Additional materials: www.superdatascience.com/563

In this episode, Jon shares his daily technical exercise, which is part of an extensive habit tracking system that allows him to achieve more, create more structure within his day, and cut out bad habits. By completing mathematics, computer science, or programming exercise daily, Jon is able to hone his technical skills in a limitlessly broad field and open new professional opportunities in the long run.Additional materials: www.superdatascience.com/562

In this episode, Ribbon Health CTO Nate Fox joins us to discuss the ins and outs of APIs. Tune in to hear him share how he and his team build out APIs from scratch; how they ensure the uptime and reliability of APIs and how they leverage machine learning to improve the quality of healthcare delivery and maximize their social impact.In this episode you will learn: What are APIs? [13:20] How Ribbon Health’s data API leverages ML models to improve the quality of healthcare delivery [16:08] How to design a data API from scratch [20:00] How to ensure the uptime and reliability of APIs [25:28] How Ribbon uses knowledge graphs, manually labeled data samples, and an XGBoost model with hundreds of inputs to assign a confidence score [27:14] Nate’s favorite tool for easily scaling up the impact of data science [37:40] What is Nate’s day-to-day like? [34:34] The qualities Nate looks for when hiring data scientists [39:50] How scientists and engineers can make a big social impact in health technology [42:50] Additional materials: www.superdatascience.com/561

In this episode, Jon shares his daily habit of reading two pages and explains how it has transformed his productivity.Additional materials: www.superdatascience.com/560

Natural language processing expert and PhD student Melanie Subbiah sits down with Jon Krohn to discuss GPT-3, its strengths and weaknesses, and the future of NLP.In this episode you will learn: What is GPT-3? [6:24] The strengths and weaknesses of GPT-3 [14:38] What is autoregression? [18:03] GPT-3's new fine-tuning abilities [20:02] Bias issues with GPT-3 [22:47] The future of natural language processing models [27:54] How Melanie ended up working at OpenAI [38:13] Melanie’s self-study process [42:19] Melanie's work on OpenAI API [45:45] How to address the climate change and bias issues that cloud discussions of large natural language models [49:40] Why Melanie chose to do a PhD at Columbia University [1:01:17] The machine learning tools Melanie’s most excited about [1:08:09] Additional materials: www.superdatascience.com/559

In this episode, Jon shares the key topics he recently discussed with the Open Data Science Conference. From the approach behind his extensive machine learning and deep learning content library to revealing the key tools and software he uses daily, get to know Jon and his process a little better.Additional materials: www.superdatascience.com/558

Pandas expert Matt Harrison sits down with Jon Krohn to discuss tips, tricks and best practices for Pandas learning and mastery.In this episode you will learn: Pros and cons of self-publishing and working with a publisher [5:05] Matt's six tips for using Pandas [17:13] The best way for corporate teams to level up their skills [40:04] How to learn anything effectively [47:14] Matt’s tricks for staying motivated [50:00] Matt’s recommendations for using Git and the Unix command line [1:00:14] Matt’s recommended software libraries for working with tabular data [1:19:45] Additional materials: www.superdatascience.com/557

Discover Jon’s extensive library of machine learning content and learn why Jon's Machine Learning House forms the knowledge structure of an outstanding data scientist or ML engineer.Additional materials: www.superdatascience.com/556

Data scientist and Youtuber Ken Jee joins Jon Krohn for a deep dive into the world of sports analytics and brings us behind the makings of his large, online data science community.In this episode you will learn: The inspiration behind Ken’s YouTube videos [18:03] Ken’s four steps for getting started in data science [24:18] How sports analytics is transforming sports like golf [33:32] Ken’s favorite tools for software scripting as well as for production code development [41:10] How the #66DaysofData hashtag can supercharge your capacity as a data scientist [42:51] Ken’s data science podcast Ken’s Nearest Neighbors [54:11] LinkedIn Q&A [1:00:32] Additional materials: www.superdatascience.com/555

In this episode, Jon shares where you can find his extensive deep learning video content and courses. Tune in to learn more about his deep learning curriculum and where you can learn for free.Additional materials: www.superdatascience.com/554