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Harness the power of MATLAB for deep-learning challenges. Practical MATLAB Deep Learning, Second Edition, remains a one-of a-kind book that provides an introduction to deep learning and using MATLAB's deep-learning toolboxes. In this book, you’ll see how these toolboxes provide the complete set of functions needed to implement all aspects of deep learning. This edition includes new and expanded projects, and covers generative deep learning and reinforcement learning.

Over the course of the book, you'll learn to model complex systems and apply deep learning to problems in those areas. Applications include:

  • Aircraft navigation
  • An aircraft that lands on Titan, the moon of Saturn, using reinforcement learning
  • Stock market prediction
  • Natural language processing
  • Music creation usng generative deep learning
  • Plasma control
  • Earth sensor processing for spacecraft
  • MATLAB Bluetooth data acquisition applied to dance physics  


What You Will Learn
  • Explore deep learning using MATLAB and compare it to algorithms
  • Write a deep learning function in MATLAB and train it with examples
  • Use MATLAB toolboxes related to deep learning
  • Implement tokamak disruption prediction
  • Now includes reinforcement learning
Who This Book Is For 

Engineers, data scientists, and students wanting a book rich in examples on deep learning using MATLAB.

Table of Contents

  1. Cover
  2. Front Matter
  3. 1. What Is Deep Learning?
  4. 2. MATLAB Machine Learning Toolboxes
  5. 3. Finding Circles with Deep Learning
  6. 4. Classifying Movies
  7. 5. Algorithmic Deep Learning
  8. 6. Tokamak Disruption Detection
  9. 7. Classifying a Pirouette
  10. 8. Completing Sentences
  11. 9. Terrain-Based Navigation
  12. 10. Stock Prediction
  13. 11. Image Classification
  14. 12. Orbit Determination
  15. 13. Earth Sensors
  16. 14. Generative Modeling of Music
  17. 15. Reinforcement Learning
  18. Back Matter