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portada Practical Matlab Deep Learning: A Projects-Based Approach
Type
Physical Book
Author
Publisher
Language
English
Pages
373
Format
Paperback
Dimensions
25.4 x 17.8 x 1.9 cm
Weight
0.61 kg.
ISBN13
9781484279113
Edition No.
0002
Categories

Practical Matlab Deep Learning: A Projects-Based Approach

Stephanie Thomas (Author) · Michael Paluszek (Author) · Eric Ham (Author) · Apress · Paperback

Practical Matlab Deep Learning: A Projects-Based Approach - Paluszek, Michael ; Thomas, Stephanie ; Ham, Eric

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Synopsis "Practical Matlab Deep Learning: A Projects-Based Approach "

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 navigationAn aircraft that lands on Titan, the moon of Saturn, using reinforcement learningStock market predictionNatural language processingMusic creation usng generative deep learningPlasma controlEarth sensor processing for spacecraftMATLAB Bluetooth data acquisition applied to dance physics What You Will LearnExplore deep learning using MATLAB and compare it to algorithmsWrite a deep learning function in MATLAB and train it with examplesUse MATLAB toolboxes related to deep learningImplement tokamak disruption predictionNow includes reinforcement learningWho This Book Is For Engineers, data scientists, and students wanting a book rich in examples on deep learning using MATLAB.

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