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

The Super Data Science Podcast: Machine Learning | AI | Success

627: AutoML: Automated Machine Learning

The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast.

As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact.

Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy.

We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.

627: AutoML: Automated Machine Learning

Super Data Science: ML & AI Podcast with Jon Krohn