Pruksachatkun, Yada
Practicing Trustworthy Machine Learning: Consistent, Transparent, and Fair AI Pipelines
- ISBN 13:
- 9781098120276
- author:
- Pruksachatkun, Yada
- format:
- Paperback
- publisher:
- O'Reilly Media
- language:
- English
- Publication Year:
- 2023
- Pages:
- 350
- Dimensions:
- 23.1 x 17.5 x 2 centimetres (0.5
- Genre:
- Computers, Social Aspects, Human-Computer Interaction,
- Condition:
- New
- Availability:
- Item usually sent within 7 working days
Description
Building Trustworthy Machine Learning Pipelines: A Practical Guide Yada Pruksachatkun, Matthew McAteer, and Subhabrata Majumdar provide a comprehensive blueprint for developing industry-grade trusted ML systems. This guide helps development teams produce models that are secure, more robust, less biased, and more explainable. You'll learn how to identify and fix fairness concerns, recognize privacy leaks in an ML pipeline, and develop ML systems that are robust against malicious attacks. The authors also cover important systemic considerations, such as managing trust debt and understanding which ML obstacles require human intervention. This book offers a practical starting point for engineers and data scientists looking to release trustworthy ML applications into the world.
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