Deep Learning Illustrated: A Visual, Interactive Guide to Artificial Intelligence, 1st edition

Published by Addison-Wesley Professional (August 5, 2019) © 2020

  • Jon Krohn
  • Grant Beyleveld
  • Aglaé Bassens
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Deep learning is one of today's hottest fields. This approach to machine learning is achieving breakthrough results in some of today's highest profile applications, in organisations ranging from Google to Tesla, Facebook to Apple. Thousands of technical professionals and students want to start leveraging its power, but previous books on deep learning have often been non-intuitive, inaccessible, and dry. In Deep Learning Illustrated, three world-class instructors and practitioners present a uniquely visual, intuitive, and accessible high-level introduction to the techniques and applications of deep learning. Packed with vibrant, full-colour illustrations, it abstracts away much of the complexity of building deep learning models, making the field more fun to learn, and accessible to a far wider audience.

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Part I's high-level overview explains what Deep Learning is, why it has become so ubiquitous, and how it relates to concepts and terminology such as Artificial Intelligence, Machine Learning, Artificial Neural Networks, and Reinforcement Learning. These opening chapters are replete with vivid illustrations, easy-to-grasp analogies, and character-focused narratives.

Building on this foundation, the authors then offer a practical reference and tutorial for applying a wide spectrum of proven deep learning techniques. Essential theory is covered with as little mathematics as possible, and illuminated with hands-on Python code. Theory is supported with practical 'run-throughs' available in accompanying Jupyter notebooks, delivering a pragmatic understanding of all major deep learning approaches and their applications: machine vision, natural language processing, image generation, and videogaming.

  • Part I: Introducing Deep Learning
  • 1. Biological and Machine Vision
  • 2. Human and Machine Language
  • 3. Machine Art
  • 4. Game-Playing Machines
  • Part II: Essential Theory Illustrated
  • 5. The (Code) Cart Ahead of the (Theory) Horse
  • 6. Artificial Neurons Detecting Hot Dogs
  • 7. Artificial Neural Networks
  • 8. Training Deep Networks
  • 9. Improving Deep Networks
  • Part III: Interactive Applications of Deep Learning
  • 10. Machine Vision
  • 11. Natural Language Processing
  • 12. Generative Adversarial Networks
  • 13. Deep Reinforcement Learning
  • Part IV: You and AI
  • 14. Moving Forward with Your Own Deep Learning

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