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Inside Deep Learning Math Algorithms Models
by Edward Raff
Foreword by Kirk Borne
April 2022
ISBN 9781617298639
600 pages
Inside Deep Learning illuminates the inner workings of deep learning algorithms in a way that even machine learning novices can understand. You’ll explore deep learning concepts and tools through plain language explanations, annotated code, and dozens of instantly useful PyTorch examples. Each type of neural network is clearly presented without complex math, and every solution in this book can run using readily available GPU hardware!
In Inside Deep Learning, you will learn how to:
Implement deep learning with PyTorch Select the right deep learning components
Train and evaluate a deep learning model
Fine tune deep learning models to maximize performance
Understand deep learning terminology
Adapt existing PyTorch code to solve new problems
Edward Raff is a Chief Scientist at Booz Allen Hamilton, and the author of the JSAT machine learning library.
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