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

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

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  • Your Price: $39.99
  • List Price: $49.99
  • Estimated Release: Sep 6, 2019

eBook (Watermarked)

  • Your Price: $31.99
  • List Price: $39.99
  • Estimated Release: Aug 9, 2019
  • Includes EPUB, MOBI, and PDF
  • About eBook Formats
  • This eBook includes the following formats, accessible from your Account page after purchase:

    ePub EPUB The open industry format known for its reflowable content and usability on supported mobile devices.

    MOBI MOBI The eBook format compatible with the Amazon Kindle and Amazon Kindle applications.

    Adobe Reader PDF The popular standard, used most often with the free Adobe® Reader® software.

    This eBook requires no passwords or activation to read. We customize your eBook by discreetly watermarking it with your name, making it uniquely yours.

About

Features

  • Ideal for software developers, data scientists, and analysts at all levels of experience
  • Teaches through simple visuals, accessible Python code examples, character-driven narratives, and intuitive analogies
  • Covers today’s leading applications, including machine vision, natural language processing, image generation, and videogames
  • Introduces four powerful Deep Learning libraries: TensorFlow, Keras, PyTorch, and Coach
  • Carefully designed to minimize mathematical formulae and avoid unnecessary complexity

Description

  • Copyright 2020
  • Dimensions: 7" x 9-1/8"
  • Pages: 416
  • Edition: 1st
  • Book
  • ISBN-10: 0-13-511669-4
  • ISBN-13: 978-0-13-511669-2

"This book is a stunning achievement, written with precision and depth of understanding. It entertains you and gives you lots of interesting information at the same time. I could never imagine understanding and gaining scientific knowledge, namely 'Deep Learning' can be this much fun! Reading the book is a pleasure and I highly recommend it."
—maryamkhakpour, O'Reilly Online Learning (Safari) Reviewer
"This title is a great resource for those looking to understand deep learning. The illustrations are helpful and aid in cementing a richer understanding of the content, and the background context surrounding biological motivations for the tools and techniques enables a greater appreciation of the field. I enthusiastically recommend this book to any and all who are interested in the topic of deep learning."
-vincepetaccio, O'Reilly Online Learning (Safari) Reviewer
Deep learning is transforming software, facilitating powerful new artificial intelligence capabilities, and driving unprecedented algorithm performance. Deep Learning Illustrated is uniquely visual, intuitive, and accessible, and yet offers a comprehensive introduction to the discipline’s techniques and applications. Packed with full-color applications and easy-to-follow code, it sweeps away much of the complexity of building deep learning models, making the subject approachable and fun to learn.

World-class instructor and practitioner Jon Krohn–with crucial material 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. He also offers a practical reference and tutorial for developers, data scientists, researchers, analysts, and students who want to start applying it. He covers essential theory with as little mathematics as possible, preferring to illuminate concepts with hands-on Python code and practical “run-throughs” in accompanying Jupyter notebooks. To help you progress quickly, he focuses on the versatile, high-level 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, deep feedforward networks, 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
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Sample Content

Table of Contents

About the Authors

Introduction

Part I: Introducing Deep Learning

Chapter 1: Biological and Machine Vision

Chapter 2: Human and Machine Language

Chapter 3: Machine Art

Chapter 4: Game-Playing Machines

Part II: Essential Theory Illustrated

Chapter 5: The (Code) Cart Ahead of the (Theory) Horse

Chapter 6: Artificial Neurons Detecting Hot Dogs

Chapter 7: Artificial Neural Networks

Chapter 8: Training Deep Networks

Chapter 9: Improving Deep Networks

Part III: Interactive Applications of Deep Learning

Chapter 10: Machine Vision

Chapter 11: Natural Language Processing

Chapter 12: Generative Adversarial Networks

Chapter 13: Deep Reinforcement Learning

Part IV: Deep Learning Libraries

Chapter 14: TensorFlow

Chapter 15: PyTorch

Part V: Artificial Intelligence

Chapter 16: Building Your Own Deep Learning Project

Part VI: Appendixes

Appendix A: Formal Neural Network Notation

Appendix B: Backpropagation

Index

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