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

627: AutoML: Automated Machine Learning 01:30:57 Share

Super Data Science: ML & AI Podcast with Jon Krohn

Shownotes Transcript

627: AutoML: Automated Machine Learning