Explainable AI for Practitioners: Designing and Implementing Explainable ML Solutions
Language: English
Published by O'Reilly Media, 2022
- Softcover
- New
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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In English.
Seller Inventory # ria9781098119133_new
- Title
- Explainable AI for Practitioners: Designing and Implementing Explainable ML Solutions
- Author
- Munn, Michael; Pitman, David
- Publisher
- O'Reilly Media
- Publication year
- 2022
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 1098119134
- ISBN 13
- 9781098119133
- Item weight
- 608 grams
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.
This essential book provides:
- A detailed look at some of the most useful and commonly used explainability techniques, highlighting pros and cons to help you choose the best tool for your needs
- Tips and best practices for implementing these techniques
- A guide to interacting with explainability and how to avoid common pitfalls
- The knowledge you need to incorporate explainability in your ML workflow to help build more robust ML systems
- Advice about explainable AI techniques, including how to apply techniques to models that consume tabular, image, or text data
- Example implementation code in Python using well-known explainability libraries for models built in Keras and TensorFlow 2.0, PyTorch, and HuggingFace
"Synopsis" may belong to another edition of this title.
About the Author
David Pitman is a staff engineer working in Google Cloud on the AI Platform, where he leads the Explainable AI team. He's also a co-organizer of PuPPy, the largest Python group in the Pacific Northwest. David has a Masters of Engineering degree and a BS in computer science from MIT, where he previously served as a research scientist.
"About the title" may belong to another edition of this title.
Ria Christie Collections
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