An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and res

This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simp

Technology is moving at an exponential pace in this era of computational intelligence. Machine learning has emerged as one of the most promising tools used to c

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, opti

Provides a practical guide to get started and execute on machine learning within a few days without necessarily knowing much about machine learning.The first fi