Gabriel Bayomi is the Co-Founder at OpenLayer, a tool that tests & debugs machine learning models. OpenLayer was in the YCombinator’s batch in 2021, building tools for machine learning model testing. Previously he was a machine learning engineer at Apple working on Siri. He has a master degree in computer science from Carnegie Mellon. He is passionate about Natural Language Processing, Machine Learning, and Computational Social Science. We talked about how to test and debug machine learning models, his experience at Apple, and career lessons. If you like the show subscribe to the channel and give us a 5-star review. Subscribe to Daliana’s newsletter on www.dalianaliu.com/ for more on data science and career.

Gabriel’s LinkedIn: https://www.linkedin.com/in/gbayomi
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0:00 Intro
00:01:39 How he got into machine learning
00:06:43 His experience at Apple, Siri
00:15:55 How to validate the solution
00:19:39 Benefits of using external error analysis framework
00:21:30 How to build a model evaluation pipeline
00:28:26 Don’t overfit the subset of data
00:33:19 Your validation set shouldn’t be fixed
00:41:03 Become one with data
00:44:05 Three model interpretability library you should use
00:50:47 Common mistakes people made in model validation
00:53:33 How to create an adversarial test
00:55:43 How to check data quality
01:06:46 Transition from engineer to executive
01:10:04 Things he learnt from his favorite coworker
01:17:57 how job roles would evolve

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