The Art and Science of Algorithms that Make Sense of Data

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. He covers a wide range of logical, geometric and statistical models, and state-of-the-art topics such as matrix factorization and ROC analysis. Particular attention is paid to the central role played by features.

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