Machine learning

The first book to present the basic techniques and main results of this expanding field of research.

Sure to be influential, this book lays the foundations for the use of algebraic geometry in statistical learning theory.

A graduate textbook that provides a unified treatment of machine learning methods and their applications in the environmental sciences.

A coherent source for applications including robotics, computational biology, graphics, manufacturing, aerospace applications and medicine.

This Element provides theoretical and practical introductions to machine learning for social scientists in applying it to experimental data.

Discover techniques for inferring unknown variables and quantities with the second volume of this extraordinary three-volume set.

Learn how cutting-edge AI and data science techniques are integrated in financial markets from leading experts in the industry.

A self-contained and practical introduction that assumes no prior knowledge of programming or machine learning.