Description: Explainable AI for Practitioners by Michael Munn, David Pitman Explainability methods provide an essential toolkit for better understanding model behavior, and this practical guide brings together best-in-class techniques for model explainability. FORMAT Paperback LANGUAGE English CONDITION Brand New Publisher Description 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 youll 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 needsTips and best practices for implementing these techniquesA guide to interacting with explainability and how to avoid common pitfallsThe knowledge you need to incorporate explainability in your ML workflow to help build more robust ML systemsAdvice about explainable AI techniques, including how to apply techniques to models that consume tabular, image, or text dataExample implementation code in Python using well-known explainability libraries for models built in Keras and TensorFlow 2.0, PyTorch, and HuggingFace Author Biography Michael Munn is a research software engineer at Google. His work focuses on better understanding the mathematical foundations of machine learning and how those insights can be used to improve machine learning models at Google. Previously, he worked in the Google Cloud Advanced Solutions Lab helping customers design, implement, and deploy machine learning models at scale. 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 staff engineer working in Google Cloud on the AI Platform, where he leads the Explainable AI team. Hes 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. Details ISBN1098119134 Author David Pitman Short Title Explainable AI for Practitioners Language English ISBN-10 1098119134 ISBN-13 9781098119133 Format Paperback Subtitle Designing and Implementing Explainable ML Solutions Year 2022 Place of Publication Sebastopol Country of Publication United States Publisher OReilly Media Imprint OReilly Media Pages 250 Publication Date 2022-11-11 AU Release Date 2022-11-11 NZ Release Date 2022-11-11 US Release Date 2022-11-11 UK Release Date 2022-11-11 DEWEY 006.31 Audience Professional & Vocational We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:139197024;
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Book Title: Explainable AI for Practitioners
