
Deep Learning
A Practical Introduction
- English
- PDF
- Available on iOS & Android
About this book
An engaging and accessible introduction to deep learning perfect for students and professionals
In Deep Learning: A Practical Introduction, a team of distinguished researchers delivers a book complete with coverage of the theoretical and practical elements of deep learning. The book includes extensive examples, end-of-chapter exercises, homework, exam material, and a GitHub repository containing code and data for all provided examples.
Combining contemporary deep learning theory with state-of-the-art tools, the chapters are structured to maximize accessibility for both beginning and intermediate students. The authors have included coverage of TensorFlow, Keras, and Pytorch. Readers will also find:
- Thorough introductions to deep learning and deep learning tools
- Comprehensive explorations of convolutional neural networks, including discussions of their elements, operation, training, and architectures
- Practical discussions of recurrent neural networks and non-supervised approaches to deep learning
- Fulsome treatments of generative adversarial networks as well as deep Bayesian neural networks
Perfect for undergraduate and graduate students studying computer vision, computer science, artificial intelligence, and neural networks, Deep Learning: A Practical Introduction will also benefit practitioners and researchers in the fields of deep learning and machine learning in general.
Frequently asked questions
- Essential is ideal for learners and professionals who enjoy exploring a wide range of subjects. Access the Essential Library with 800,000+ trusted titles and best-sellers across business, personal growth, and the humanities. Includes unlimited reading time and Standard Read Aloud voice.
- Complete: Perfect for advanced learners and researchers needing full, unrestricted access. Unlock 1.4M+ books across hundreds of subjects, including academic and specialized titles. The Complete Plan also includes advanced features like Premium Read Aloud and Research Assistant.
Please note we cannot support devices running on iOS 13 and Android 7 or earlier. Learn more about using the app.
Information
Table of contents
- Cover
- Title Page
- Copyright
- Contents
- About the Authors
- Foreword
- Preface
- Acknowledgment
- About the Companion Website
- Chapter 1 The Multilayer Perceptron
- Chapter 2 Training Practicalities
- Chapter 3 Deep Learning Tools
- Chapter 4 Convolutional Neural Networks
- Chapter 5 Recurrent Neural Networks
- Chapter 6 Attention Networks and Transformers
- Chapter 7 Deep Unsupervised Learning I
- Chapter 8 Deep Unsupervised Learning II
- Chapter 9 Deep Bayesian Networks
- List of Acronyms
- Notation
- Bibliography
- Index
- EULA