Traditional books on machine learning can be divided into two groups- those aimed at advanced undergraduates or early postgraduates with reasonable mathematical

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

Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about

An intuitive approach to machine learning covering key concepts, real-world applications, and practical Python coding exercises.

This book will guide you from the theoretical underpinnings of hands-on nutrition education (HONE) programs to the tools necessary to turn that theory into prac