Deep Learning Illustrated: A Visual, Interactive Guide to Artificial Intelligence

by Jon Krohn, Grant Beyleveld, Aglaé Bassens

Overview

"The authors’ clear visual style provides a comprehensive look at what’s currently possible with artificial neural networks as well as a glimpse of the magic that’s to come."
– Tim Urban, author of Wait But Why

Fully Practical, Insightful Guide to Modern Deep Learning

Deep learning is transforming software, facilitating powerful new artificial intelligence capabilities, and driving unprecedented algorithm performance. Deep Learning Illustrated is uniquely intuitive and offers a complete introduction to the discipline’s techniques. Packed with full-color figures and easy-to-follow code, it sweeps away the complexity of building deep learning models, making the subject approachable and fun to learn.

World-class instructor and practitioner Jon Krohn–with visionary content from Grant Beyleveld and beautiful illustrations by Aglaé Bassens–presents straightforward analogies to explain what deep learning is, why it has become so popular, and how it relates to other machine learning approaches. Krohn has created a practical reference and tutorial for developers, data scientists, researchers, analysts, and students who want to start applying it. He illuminates theory with hands-on Python code in accompanying Jupyter notebooks. To help you progress quickly, he focuses on the versatile deep learning library Keras to nimbly construct efficient TensorFlow models; PyTorch, the leading alternative library, is also covered.

You’ll gain a pragmatic understanding of all major deep learning approaches and their uses in applications ranging from machine vision and natural language processing to image generation and game-playing algorithms.

• Discover what makes deep learning systems unique, and the implications for practitioners
• Explore new tools that make deep learning models easier to build, use, and improve
• Master essential theory: artificial neurons, training, optimization, convolutional nets, recurrent nets, generative adversarial networks (GANs), deep reinforcement learning, and more
• Walk through building interactive deep learning applications, and move forward with your own artificial intelligence projects

Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

Product Details

ISBN-13:	9780135121726
Publisher:	Pearson Education
Publication date:	08/05/2019
Series:	Addison-Wesley Data & Analytics Series
Sold by:	Barnes & Noble
Format:	eBook
Pages:	416
File size:	21 MB
Note:	This product may take a few minutes to download.
Age Range:	18 Years

About the Author

Jon Krohn is the chief data scientist at untapt, a machine learning startup in New York. He leads a flourishing Deep Learning Study Group, presents the acclaimed Deep Learning with TensorFlow LiveLessons in Safari, and teaches his Deep Learning curriculum at the NYC Data Science Academy. Jon holds a doctorate in neuroscience from Oxford University and has been publishing on machine learning in leading academic journals since 2010.

 

Grant Beyleveld is a doctoral candidate at the Icahn School of Medicine at New York’s Mount Sinai hospital, researching the relationship between viruses and their hosts. A founding member of the Deep Learning Study Group, he holds a masters in molecular medicine and medical biochemistry from the University of Witwatersrand.

 

Aglaé Bassens is a Belgian artist based in Brooklyn. She studied fine arts at The Ruskin School of Drawing and Fine Art, Oxford University, and University College London’s Slade School of Fine Arts. Along with her work as an illustrator, her practice includes still life painting and murals.

Table of Contents

• Part I: Introducing Deep Learning
• 1. Biological and Machine Vision
• 2. Human and Machine Language
• 3. Human and Machine Art
• 4. Game-Playing Machines Backgammon Atari Go
• Part II: Essential Theory Illustrated
• 5. Artificial Neurons
• 6. Artificial Neural Networks
• 7. Training Deep Networks
• 8. Improving Deep Networks
• Part III: Interactive Applications
• 9. Machine Vision
• 10. Natural Language Processing
• 11. Generative Adversarial Networks
• 12. Reinforcement Learning
• Part IV: Deep Learning Libraries
• 13. TensorFlow
• 14. PyTorch
• Part V: Artificial Intelligence
• 15. Deep Learning and the AI Revolution
• 16. Building Your Own Deep Learning Project

Editorial Reviews

Over the next few decades, artificial intelligence is poised to dramatically change almost every aspect of our lives, in large part due to today’s breakthroughs in deep learning. The authors’ clear visual style provides a comprehensive look at what’s currently possible with artificial neural networks as well as a glimpse of the magic that’s to come.”
—Tim Urban, writer and illustrator of Wait But Why

“This book is an approachable, practical, and broad introduction to deep learning, and the most beautifully illustrated machine learning book on the market.”
—Dr. Michael Osborne, Dyson Associate Professor in Machine Learning, University of Oxford

“This book should be the first stop for deep learning beginners, as it contains lots of concrete, easy-to-follow examples with corresponding tutorial videos and code notebooks. Strongly recommended.”
—Dr. Chong Li, cofounder, Nakamoto & Turing Labs; adjunct professor, Columbia University

“It’s hard to imagine developing new products today without thinking about enriching them with capabilities using machine learning. Deep learning in particular has many practical applications, and this book’s intelligible clear and visual approach is helpful to anyone who would like to understand what deep learning is and how it could impact your business and life for years to come.”
—Helen Altshuler, engineering leader, Google

“This book leverages beautiful illustrations and amusing analogies to make the theory behind deep learning uniquely accessible. Its straightforward example code and best-practice tips empower readers to immediately apply the transformative technique to their particular niche of interest.”
–Dr. Rasmus Rothe, founder, Merantix

“This is an invaluable resource for anyone looking to understand what deep learning is and why it powers almost every automated application today, from chatbots and voice recognition tools to self-driving cars. The illustrations and biological explanations help bring to life a complex topic and make it easier to grasp fundamental concepts.”
–Joshua March, CEO and cofounder, Conversocial; author of Message Me

“Deep learning is regularly redefining the state of the art across machine vision, natural language, and sequential decision-making tasks. If you too would like to pass data through deep neural networks in order to build high-performance models, then this book–with its innovative, highly visual approach–is the ideal place to begin.”
–Dr. Alex Flint, roboticist and entrepreneur

From the Publisher