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Machine Learning: The Art and Science of Algorithms that Make Sense of Data

Users: 1 - Average Rating: 4.00

As one of the most comprehensive machine learning texts around, this book does justice to the field's incredible richness, but without losing sight of the unifying principles. Peter Flach's clear, example-based approach begins by discussing how a spam filter works, which gives an immediate introduction to machine learning in action, with a minimum of technical fuss. Flach provides case studies of increasing complexity and variety with well-chosen examples and illustrations throughout. He covers a wide range of logical, geometric and statistical models and state-of-the-art topics such as matrix factorisation and ROC analysis. Particular attention is paid to the central role played by features. The use of established terminology is balanced with the introduction of new and useful concepts, and summaries of relevant background material are provided with pointers for revision if necessary. These features ensure Machine Learning will set a new standard as an introductory textbook..


Machine Learning

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Author of the review:
Spiros Sirmakessis
University of Peloponnese


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Giulia Cademartori

Very clear and systematic overview of the major machine learning methods with a focus on the mathematical foundations behind the algorithms. This book is suitable for people who are interested in going deeper in Machine Learning theory more than in applications and coding.