This book is the first to examine the history of imaginative thinking about intelligent machines, featuring contributions from... Læs mere
A project-based guide to the basics of deep learning.
An argument in favor of finding a place for humans (and humanness) in the future digital economy.
This practical introduction for final-year undergraduate and graduate students is ideally suited to computer scientists without a background in calculus and... Læs mere
Containing numerous algorithms and major theorems, this step-by-step guide covers the fundamentals of kernel-based learning theory. Including over two hundred... Læs mere
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives.
Designed for researchers and graduate students in machine learning, this book introduces the theory of variational Bayesian learning, a popular machine learning... Læs mere
The book provides explanations of principles of time-proven machine learning algorithms applied in text mining together with step-by-step... Læs mere