Jon Krohn speaks with Erin LeDell, H2O.ai’s Chief Machine Learning Scientist. They investigate how AutoML supercharges the data science process, the importance of admissible machine learning for an equitable data-driven future, and what Erin’s group Women in Machine Learning & Data Science is doing to increase inclusivity and representation in the field. This episode is brought to you by Datalore (https://datalore.online/SDS), the collaborative data science platform. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • The H2O AutoML platform Erin developed [07:43] • How genetic algorithms work [19:17] • Why you should consider using AutoML? [28:15] • The “No Free Lunch Theorem” [33:45] • What Admissible Machine Learning is [37:59] • What motivated Erin to found R-Ladies Global and Women in Machine Learning and Data Science [47:00] • How to address bias in datasets [57:03] Additional materials: www.superdatascience.com/627