Dive into Deep Learning
- Authors:
- Aston Zhang, Amazon Web Services
- Zachary C. Lipton, Carnegie Mellon University, Pennsylvania
- Mu Li, Amazon Web Services
- Alexander J. Smola, Amazon Web Services
- Date Published: February 2024
- availability: Available
- format: Paperback
- isbn: 9781009389433
Paperback
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Deep learning has revolutionized pattern recognition, introducing tools that power a wide range of technologies in such diverse fields as computer vision, natural language processing, and automatic speech recognition. Applying deep learning requires you to simultaneously understand how to cast a problem, the basic mathematics of modeling, the algorithms for fitting your models to data, and the engineering techniques to implement it all. This book is a comprehensive resource that makes deep learning approachable, while still providing sufficient technical depth to enable engineers, scientists, and students to use deep learning in their own work. No previous background in machine learning or deep learning is required—every concept is explained from scratch and the appendix provides a refresher on the mathematics needed. Runnable code is featured throughout, allowing you to develop your own intuition by putting key ideas into practice.
Read more- Starting from scratch, teaches the concepts and context needed to understand and use deep learning
- Combines the high-quality exposition expected of a textbook with the interactivity of a hands-on tutorial
- Accompanied by a software library with clean runnable code in multiple deep learning frameworks and complemented by an online forum for interactive discussion of technical details and questions that arise
Reviews & endorsements
'In less than a decade, the AI revolution has swept from research labs to broad industries to every corner of our daily life. Dive into Deep Learning is an excellent text on deep learning and deserves attention from anyone who wants to learn why deep learning has ignited the AI revolution: the most powerful technology force of our time.' Jensen Huang, Founder and CEO, NVIDIA
See more reviews'This is a timely, fascinating book, providing not only a comprehensive overview of deep learning principles but also detailed algorithms with hands-on programming code, and moreover, a state-of-the-art introduction to deep learning in computer vision and natural language processing. Dive into this book if you want to dive into deep learning!' Jiawei Han, Michael Aiken Chair Professor, University of Illinois at Urbana-Champaign
'This is a highly welcome addition to the machine learning literature, with a focus on hands-on experience implemented via the integration of Jupyter notebooks. Students of deep learning should find this invaluable to become proficient in this field.' Bernhard Schölkopf,, Director, Max Planck Institute for Intelligent Systems
'Dive into Deep Learning strikes an excellent balance between hands-on learning and in-depth explanation. I've used it in my deep learning course and recommend it to anyone who wants to develop a thorough and practical understanding of deep learning.' Colin Raffel, Assistant Professor, University of North Carolina, Chapel Hill
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×Product details
- Date Published: February 2024
- format: Paperback
- isbn: 9781009389433
- length: 574 pages
- dimensions: 254 x 203 x 25 mm
- weight: 1.38kg
- availability: Available
Table of Contents
Installation
Notation
1. Introduction
2. Preliminaries
3. Linear neural networks for regression
4. Linear neural networks for classification
5. Multilayer perceptrons
6. Builders guide
7. Convolutional neural networks
8. Modern convolutional neural networks
9. Recurrent neural networks
10. Modern recurrent neural networks
11. Attention mechanisms and transformers
Appendix. Tools for deep learning
Bibliography
Index.-
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Dive into Deep Learning
Aston Zhang, Zachary C. Lipton, Mu Li, Alexander J. Smola
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