Explainable AI for Practitioners: Designing and Implementing Explainable ML Solutions - Softcover

Munn, Michael; Pitman, David

Softcover

ISBN 10: 1098119134 ISBN 13: 9781098119133

Publisher: O'Reilly Media, 2022

Synopsis

Most intermediate-level machine learning books focus on how to optimize models by increasing accuracy or decreasing prediction error. But this approach often overlooks the importance of understanding why and how your ML model makes the predictions that it does. Explainability methods provide an essential toolkit for better understanding model behavior, and this practical guide brings together best-in-class techniques for model explainability. Experienced machine learning engineers and data scientists will learn hands-on how these techniques work so that you'll be able to apply these tools more easily in your daily workflow.

About this title

About the Author

Michael Munn is an ML Solutions Engineer at Google where he works with customers of Google Cloud on helping them design, implement, and deploy machine learning models. He also teaches an ML Immersion Program at the Advanced Solutions Lab. Michael has a PhD in mathematics from the City University of New York. Before joining Google, he worked as a research professor. David Pitman is a Senior Engineering Manager working in Google Cloud on the AI Platform, where he leads the Explainable AI team. He is also a co-organizer of PuPPy, the largest Python group in the Pacific Northwest. David has a M.Eng. and BS in Computer Science, focusing in AI and Human-Computer Interaction, from MIT, where he was previously a research scientist.

Edition details

• Publisher: O'Reilly Media
• Publication date: 2022
• Language: English
• ISBN 10: 1098119134
• ISBN 13: 9781098119133
• Binding: Paperback
• Edition number: 1
• Number of pages: 250