Deep Learning (Adaptive Computation and Machine Learning Series)

Deep Learning (Adaptive Computation and Machine Learning Series) is a comprehensive reference focused on deep learning, neural networks, and modern artificial intelligence technologies. Written by Ian Goodfellow, Yoshua Bengio, and Aaron Courville, this publication explores the theoretical foundations and practical concepts that support contemporary machine learning systems.

The book examines key principles related to machine learning, neural network design, optimization methods, and computational learning techniques. Content is organized to provide readers with a structured understanding of deep learning models and the mathematical concepts that support their development and application.

Readers can explore topics associated with deep neural networks, representation learning, convolutional networks, sequence modeling, and machine learning architectures. The publication also discusses methods used in artificial intelligence research, data-driven systems, and advanced computational learning applications.

Suitable for students, researchers, educators, and technology professionals, this resource provides extensive coverage of deep learning concepts used across artificial intelligence, data science, computer vision, and natural language processing fields.

Topics Covered

• Deep learning fundamentals
• Neural network architectures
• Machine learning principles
• Optimization algorithms
• Deep neural network training
• Representation learning
• Convolutional neural networks
• Sequence modeling concepts
• Artificial intelligence applications
• Computational learning methods

Product Details

• Author: Ian Goodfellow; Yoshua Bengio; Aaron Courville
• ISBN-13: 9780262035613
• ISBN-10: 0262035618
• Series: Adaptive Computation and Machine Learning
• Title: Deep Learning
• Language: English
• Category: Artificial Intelligence
• Subject: Deep Learning and Machine Learning

Product Type

Artificial Intelligence