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Machine Learning Evaluation: Towards Reliable and Responsible AI

By (author) Nathalie Japkowicz, By (author) Zois Boukouvalas

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normal price: R 2 601.95

Price: R 2 471.95


| book 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.

| product details |



Normally shipped | This title will be printed on demand for your order. Delivery will be 6 weeks or less.
Publisher | Cambridge University Press
Published date | 21 Nov 2024
Language |
Format | Hardback
Pages | 426
Dimensions | 250 x 175 x 28mm (L x W x H)
Weight | 860g
ISBN | 978-1-3165-1886-1
Readership Age |
BISAC |


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Normally shipped | Available from overseas. Usually dispatched in 14 days
Readership Age |
Normal Price | R 2 723.95
Price | R 2 587.95 | on special |



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