Book description
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
- 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
Table of contents
- Cover
- Front Matter
- 1. What Is Deep Learning?
- 2. MATLAB Machine Learning Toolboxes
- 3. Finding Circles with Deep Learning
- 4. Classifying Movies
- 5. Algorithmic Deep Learning
- 6. Tokamak Disruption Detection
- 7. Classifying a Pirouette
- 8. Completing Sentences
- 9. Terrain-Based Navigation
- 10. Stock Prediction
- 11. Image Classification
- 12. Orbit Determination
- 13. Earth Sensors
- 14. Generative Modeling of Music
- 15. Reinforcement Learning
- Back Matter
Product information
- Title: Practical MATLAB Deep Learning: A Projects-Based Approach
- Author(s):
- Release date: September 2022
- Publisher(s): Apress
- ISBN: 9781484279120
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