The emphasis of the book is on the question of Why – only if why an algorithm is successful is understood, can it be properly applied, and the results trusted
AN INTRODUCTION TO MACHINE LEARNING THAT INCLUDES THE FUNDAMENTAL TECHNIQUES, METHODS, AND APPLICATIONS PROSE Award Finalist 2019 Association of American Publis
A coherent introduction to core concepts and deep learning techniques that are critical to academic research and real-world applications.
Introduction -- Supervised learning -- Bayesian decision theory -- Parametric methods -- Multivariate methods -- Dimensionality reduction -- Clustering -- Nonpa
A project-based guide to the basics of deep learning. This concise, project-driven guide to deep learning takes readers through a series of program-writing task
