£32.16

Cambridge University Press Machine Learning Evaluation: Towards Reliable and Responsible AI

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£52.37 £21.68 £28.38 £35.07 £41.77 £48.46 £55.16 25 April 2026 13 May 2026 01 June 2026 20 June 2026 09 July 2026

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Description

As machine learning applications gain widespread adoption and integration in a variety of applications, including safety and mission-critical systems, the need for robust evaluation methods grows more urgent. This book compiles scattered information on the topic from research papers and blogs to provide a centralized resource that is accessible to students, practitioners, and researchers across the sciences. The book examines meaningful metrics for diverse types of learning paradigms and applications, unbiased estimation methods, rigorous statistical analysis, fair training sets, and meaningful explainability, all of which are essential to building robust and reliable machine learning products. In addition to standard classification, the book discusses unsupervised learning, regression, image segmentation, and anomaly detection. The book also covers topics such as industry-strength evaluation, fairness, and responsible AI. Implementations using Python and scikit-learn are available on the book's website.

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Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
21 November 2024
Listed Since
04 March 2024

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