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 (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)
