Practical MATLAB Deep Learning: A Project-Based Approach, 2nd edition
Michael Paluszek, Princeton Satellite Systems;
Stephanie Thomas, Princeton Satellite Systems;
Eric Ham, Princeton Satellite Systems
Apress, 2022
ISBN: 9781484279113;
Language: English
Harness the power of MATLAB for deep-learning challenges. Practical MATLAB Deep Learning, provides an introduction to deep learning and using the Deep Learning Toolbox to solve many projects. 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
You will:
- 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
