Deep Learning (Adaptive Computation and Machine Learning series)
- Goodfellow, Ian
- Bengio, Yoshua
- Courville, Aaron
- The MIT Press
- Nov 18, 2016
The book "Deep Learning" is a comprehensive guide to the mathematical and conceptual background of deep learning, including techniques used in industry and research perspectives. It covers a broad range of topics such as linear algebra, probability theory, numerical computation, machine learning, and more. The book also offers research perspectives, covering theoretical topics such as autoencoders, Monte Carlo methods, and deep generative models. This book is a valuable resource for both undergraduate and graduate students planning careers in industry or research, as well as software engineers who want to begin using deep learning in their products or platforms.