Deep Learning is a comprehensive reference book on artificial intelligence, machine learning and neural networks, written by leading AI researchers Ian Goodfellow, Yoshua Bengio and Aaron Courville. Published by MIT Press as part of the Adaptive Computation and Machine Learning series, this widely recognized textbook provides an in-depth introduction to modern deep learning theory, mathematics and real-world applications.
Designed for university students, researchers, software engineers and AI professionals, this 800-page textbook covers the mathematical foundations of deep learning, including linear algebra, probability, information theory, optimization and machine learning algorithms. Readers will also explore practical neural network architectures, deep feedforward networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), sequence modeling, regularization techniques and optimization methods.
The book includes extensive coverage of artificial intelligence applications such as computer vision, natural language processing (NLP), speech recognition, recommendation systems, bioinformatics and video game AI. Advanced chapters introduce representation learning, autoencoders, probabilistic models, generative models, Monte Carlo methods and current deep learning research topics.
Key Features:
- 800-page comprehensive deep learning textbook
- Covers machine learning and artificial intelligence fundamentals
- Neural networks, CNNs, RNNs and deep learning architectures
- Linear algebra, probability and optimization concepts
- Computer vision and natural language processing applications
- Practical machine learning methodologies
- Suitable for students, researchers and software engineers
- Part of the Adaptive Computation and Machine Learning series
Product Details:
Title: Deep Learning
Series: Adaptive Computation and Machine Learning
Authors: Ian Goodfellow, Yoshua Bengio, Aaron Courville
Publisher: The MIT Press
Publication Date: November 2016
Language: English
Format: Paperback
Print Length: 800 Pages
ISBN-13: 9780262337373
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