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Practical MATLAB Deep Learning - Michael Paluszek - Bog

- A Projects-Based Approach

Bag om Practical MATLAB Deep 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, yoüll 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 What You Will LearnExplore 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.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9781484279113
  • Indbinding:
  • Paperback
  • Sideantal:
  • 329
  • Udgivet:
  • 11. September 2022
  • Udgave:
  • 2
  • Størrelse:
  • 252x177x31 mm.
  • Vægt:
  • 666 g.
  • 8-11 hverdage.
  • 17. Oktober 2024
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Beskrivelse af Practical MATLAB Deep 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, yoüll 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

What You Will LearnExplore 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.

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