Ranked #14 in Machine Learning, Ranked #20 in Data Science — see more rankings.

During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the...

more## Reviews and Recommendations

We've comprehensively compiled reviews of *The Elements of Statistical Learning* from the world's leading experts.

Nassim Nicholas Taleb AuthorVery comprehensive, sufficiently technical to get most of the plumbing behind machine learning. Very useful as a reference book (actually, there is no other complete reference book). The authors are the real thing (Tibshirani is the one behind the LASSO regularization technique). Uses some mathematical statistics without the burdens of measure theory and avoids the obvious but complicated proofs. I own two copies of this edition, one for the office, one for my house, and the authors generously provide the PDF for travelers like me. (Source)

## Rankings by Category

The Elements of Statistical Learning is ranked in the following categories:

- #68 in Bioinformatics
- #41 in Biostatistics
- #35 in Data Mining
- #25 in Statistics