Introduction to Explainable AI (ML Tech Talks)

This talk introduces the field of Explainable AI, outlines a taxonomy of ML interpretability methods, walks through an implementation deepdive of Integrated Gradients, and concludes with discussion on picking attribution baselines and future research directions. Chapters: 00:00 - Intro 2:31 - What is Explainable AI? 8:40 - Interpretable ML methods 14:52 - Deepdive: Integrated Gradients (IG) 39:13 - Picking baselines and future research directions Resources: Integrated gradients → Vertex AI → What-if-tool → Catch more ML Tech Talks → Subscribe to TensorFlow →