Practical MATLAB Deep Learning: A Projects-Based Approach Paperback - 2022
by Michael Paluszek; Stephanie Thomas; Eric Ham
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From the publisher
From the rear cover
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
Details
- Title Practical MATLAB Deep Learning: A Projects-Based Approach
- Author Michael Paluszek; Stephanie Thomas; Eric Ham
- Binding Paperback
- Pages 329
- Volumes 1
- Language ENG
- Publisher Apress
- Publication date 2022-09-11
- Illustrated Yes
- Features Illustrated
- ISBN 9781484279113 / 1484279115
- Weight 1.35 lbs (0.61 kg)
- Dimensions 10 x 7 x 0.73 in (25.40 x 17.78 x 1.85 cm)
- Category Computers - General Information
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