We talked about:

Christoph’s background Kaggle and other competitions How Christoph became interested in interpretable machine learning Interpretability vs Accuracy Christoph’s current competition engagement How Christoph chooses topics for books Why Christoph started the writing journey with a book Self-publishing vs via a publisher Christoph’s other books What is conformal prediction? Christoph’s book on SHAP Explainable AI vs Interpretable AI Working alone vs with other people Christoph’s other engagements and how to stay hands-on Keeping a logbook Does one have to be an expert on the topic to write a book about it? Writing in the open and other feedback gathering methods Advice for those who want to be technical writers Self-publishing tools Finding Christoph online

Links:

LinkedIn: https://www.linkedin.com/in/christoph-molnar/ Website: https://christophmolnar.com/

Free ML Engineering course: http://mlzoomcamp.com Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

Interpretability Machine learning has shown a rapid expansion into every sector and industry. With increasing reliance on models and increasing stakes for the decisions of models, questions of how models actually work are becoming increasingly important to ask. Welcome to Data Skeptic Interpretability. In this episode, Kyle interviews Christoph Molnar about his book Interpretable Machine Learning. Thanks to our sponsor, the Gartner Data & Analytics Summit going on in Grapevine, TX on March 23 – 26, 2020. Use discount code: dataskeptic. Music Our new theme song is #5 by Big D and the Kids Table. Incidental music by Tanuki Suit Riot.