£32.03

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£32 today · was £35 last week · was £43 last month

Cambridge University Press Cambridge Machine Learning Book for Engineers and Scientists

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Last 89 days · 89 data points

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£43.29 £12.96 £19.58 £26.20 £32.81 £39.43 £46.05 28 July 2026 19 August 2026 10 September 2026 02 October 2026 24 October 2026
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Price distribution over 89 days • 4 price ranges

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27 days 13 days · current 19 days 30 days 0 8 15 23 30 £16-21 £27-32 £32-38 £38-43 Days at Price

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Most common range: £38-43 (30 days, 33.7%)

Price range: £16 - £43

Price levels: 4 price ranges over 89 days

Description

Master the fundamentals of machine learning with this comprehensive guide from Cambridge University Press. Designed specifically for engineers and scientists, this book provides a coherent statistical framework to help you navigate complex data science concepts. Whether you are looking to understand basic algorithms or move into advanced modeling, this text offers a structured path for learners with a foundation in linear algebra, statistics, and programming. This resource covers a wide range of essential topics. You will learn supervised methods including k-NN, decision trees, and linear regression, as well as advanced techniques like deep neural networks and support vector machines. The book also addresses unsupervised methods such as PCA and generative adversarial networks. With careful explanations and pseudo-code, it serves as a practical tool for anyone looking to apply machine learning to real-world scientific and engineering problems.

Key Features

Comprehensive coverage of supervised learning methods ranging from fundamental k-NN and decision trees to advanced deep neural networks.

Includes essential unsupervised learning techniques such as k-means, PCA, autoencoders, and generative adversarial networks.

Structured specifically for readers with a background in linear algebra, probability, statistics, and programming.

Provides a coherent statistical framework to help you understand the mathematical foundations of machine learning.

Features careful explanations and pseudo-code to assist in understanding complex algorithmic processes.

Covers advanced modeling topics including Gaussian processes, random forests, and boosting for specialized applications.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
31 March 2022
Listed Since
26 August 2021

Barcode

No barcode data available

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