Practical MATLAB Deep Learning A Projects-Based Approach-Quality Guarantee
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Practical MATLAB Deep Learning A Projects-Based Approach-Quality Guarantee

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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 MATLABs deep-learning toolboxes. In this book, youll 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, youll 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.

Author: Michael Paluszek, Stephanie Thomas, Eric Ham
Binding Type: Paperback
Publisher: Apress
Published: 09/11/2022
Pages: 329
Weight: 1.35lbs
Size: 10.00h x 7.00w x 0.73d
ISBN: 9781484279113
Language: English

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