Fundamental topics in machine learning are presented along with theoretical and conceptual tools for the discussion and proof of algorithms. This graduate-level

This book provides conceptual understanding of machine learning algorithms though supervised, unsupervised, and advanced learning techniques. The book consists

Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with

"The authors’ clear visual style provides a comprehensive look at what’s currently possible with artificial neural networks as well as a glimpse of the magi

The first book of its kind to review the current status and future direction of the exciting new branch of machine learning/data mining called imbalanced learni