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(Ebook) Inside Deep Learning: Math, Algorithms, Models by Edward Raff ISBN 9781617298639, 1617298638

  • SKU: EBN-43565358
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Instant download (eBook) Inside Deep Learning: Math, Algorithms, Models after payment.
Authors:Edward Raff
Pages:580 pages.
Year:2022
Editon:1
Publisher:Manning Publications
Language:english
File Size:33.58 MB
Format:epub
ISBNS:9781617298639, 1617298638
Categories: Ebooks

Product desciption

(Ebook) Inside Deep Learning: Math, Algorithms, Models by Edward Raff ISBN 9781617298639, 1617298638

Journey through the theory and practice of modern deep learning, and apply innovative techniques to solve everyday data problems.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 problemsInside Deep Learning is an accessible guide to implementing deep learning with the PyTorch framework. It demystifies complex deep learning concepts and teaches you to understand the vocabulary of deep learning so you can keep pace in a rapidly evolving field. No detail is skipped—you’ll dive into math, theory, and practical applications. Everything is clearly explained in plain English.Deep learning doesn’t have to be a black box! Knowing how your models and algorithms actually work gives you greater control over your results. And you don’t have to be a mathematics expert or a senior data scientist to grasp what’s going on inside a deep learning system. This book gives you the practical insight you need to understand and explain your work with confidence.About the bookInside 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!What's inside• 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
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