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 → https://goo.gle/2PxfRtq
Vertex AI → https://goo.gle/3ifu7S5
What-if-tool → https://goo.gle/3ehZWbZ

Catch more ML Tech Talks → http://goo.gle/ml-tech-talks
Subscribe to TensorFlow → https://goo.gle/TensorFlow

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