The Elements of Statistical Learning by Trevor Hastie, Robert Tibshirani, Jerome Friedman

The Elements of Statistical Learning by Trevor Hastie, Robert Tibshirani, Jerome Friedman

This dense, rigorous reference covers the mathematical foundations of statistical learning and data mining — regression, classification, support vector machines, boosting, neural networks and more — aimed at graduate students and practitioners who need the underlying theory rather than a practical coding tutorial.

Written by three of the field's most influential statisticians, it has become a standard reference cited across machine learning and statistics courses worldwide, valued for its mathematical precision and for tying together methods that are often taught in isolation elsewhere.

A foundational graduate-level reference in statistical learning and data mining.

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