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Practical MATLAB Deep Learning A Projects-Based Approach, Second Edition [#467708]
Practical MATLAB Deep Learning: A Projects-Based Approach, Second Edition by Michael Paluszek, Stephanie Thomas, Eric Ham
English | PDF(True) | 2022 | 338 Pages | ISBN : 1484279115 | 14.5 MB
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.
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
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
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