<p><span>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, youβll see how these toolboxes provide the complete
Practical MATLAB Deep Learning: A Projects-Based Approach
β Scribed by Michael Paluszek, Stephanie Thomas, Eric Ham
- Publisher
- Apress
- Year
- 2022
- Tongue
- English
- Leaves
- 348
- Edition
- 2
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
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, youβll 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 physicsΒ Β
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 ForΒ
Engineers, data scientists, and students wanting a book rich in examples on deep learning using MATLAB.
π SIMILAR VOLUMES
<p><span>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, youβll see how these toolboxes provide the complete
Harness the power of MATLAB for deep-learning challenges. This book provides an introduction to deep learning and using MATLAB's deep-learning toolboxes. You'll see how these toolboxes provide the complete set of functions needed to implement all aspects of deep learning. <br />Along the way, you'll
<div>Harness the power of MATLAB for deep-learning challenges. This book provides an introduction to deep learning and using MATLAB's deep-learning toolboxes. Youβll see how these toolboxes provide the complete set of functions needed to implement all aspects of deep learning.Β </div><div><br></div><
<span>Harness the power of MATLAB for deep-learning challenges. This book provides an introduction to deep learning and using MATLAB's deep-learning toolboxes. You'll see how these toolboxes provide the complete set of functions needed to implement all aspects of deep learning. <br>Along the way, yo
Work with advanced topics in deep learning, such as optimization algorithms, hyper-parameter tuning, dropout, and error analysis as well as strategies to address typical problems encountered when training deep neural networks. You'll begin by studying the activation functions mostly with a single ne