Discussion on Stacked Algorithms in Machine Learning

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