Deep Learning

Key Features

• Comprehensive guide to deep learning and neural network fundamentals
• Covers topics like convolutional networks, recurrent networks, and optimization
• Combines mathematical theory with practical machine learning applications
• Ideal for students, researchers, and AI/ML professionals

Book Description

This book is a definitive resource for understanding deep learning, one of the most advanced fields in artificial intelligence. It explains how neural networks learn from data and make intelligent predictions.

The content covers core concepts such as supervised and unsupervised learning, backpropagation, and deep neural architectures. It provides both theoretical foundations and practical insights for building modern AI systems.

Widely used in universities and industry, the book is suitable for beginners with basic mathematical knowledge as well as advanced learners. It helps readers develop strong analytical and implementation skills in machine learning.

Overall, this book serves as an essential guide for mastering deep learning and applying it to real-world problems.

Product Details

• Title: Deep Learning
• Author: Ian Goodfellow, Yoshua Bengio, Aaron Courville
• Publisher: MIT Press
• Language: English
• Binding: Paperback
• Number of Pages: 800 pages
• ISBN-10: 0262035618
• ISBN-13: 978-0262035613
• Publisher Date: November 2016
• Weight: 2.7 pounds

Physical Specifications

• Height: 9.40 inches
• Width: 7.30 inches
• Spine Width: 1.60 inches