Deep Learning from Scratch : Building with Python from First Principles
Language: English
Published by O'reilly Media Okt 2019, 2019
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
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Add to basketItem description from seller
Neuware - With the resurgence of neural networks in the 2010s, deep learning has become essential for machine learning practitioners and even many software engineers. This book provides a comprehensive introduction for data scientists and software engineers with machine learning experience. You'll start with deep learning basics and move quickly to the details of important advanced architectures, implementing everything from scratch along the way.Author Seth Weidman shows you how neural networks work using a first principles approach. You'll learn how to apply multilayer neural networks, convolutional neural networks, and recurrent neural networks from the ground up. With a thorough understanding of how neural networks work mathematically, computationally, and conceptually, you'll be set up for success on all future deep learning projects.This book provides:- Extremely clear and thorough mental modelsaccompanied by working code examples and mathematical explanationsfor understanding neural networks- Methods for implementing multilayer neural networks from scratch, using an easy-to-understand object-oriented framework- Working implementations and clear-cut explanations of convolutional and recurrent neural networks- Implementation of these neural network concepts using the popular PyTorch framework.…
Seller Inventory # 9781492041412
- Title
- Deep Learning from Scratch : Building with Python from First Principles
- Author
- Seth Weidman
- Publisher
- O'reilly Media Okt 2019
- Publication year
- 2019
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 1492041416
- ISBN 13
- 9781492041412
- Item weight
- 439 grams
- Dimensions
- 233x179x21 mm
With the resurgence of neural networks in the 2010s, deep learning has become essential for machine learning practitioners and even many software engineers. This book provides a comprehensive introduction for data scientists and software engineers with machine learning experience. Youâ ll start with deep learning basics and move quickly to the details of important advanced architectures, implementing everything from scratch along the way.
Author Seth Weidman shows you how neural networks work using a first principles approach. Youâ ll learn how to apply multilayer neural networks, convolutional neural networks, and recurrent neural networks from the ground up. With a thorough understanding of how neural networks work mathematically, computationally, and conceptually, youâ ll be set up for success on all future deep learning projects.
This book provides:
- Extremely clear and thorough mental modelsâ accompanied by working code examples and mathematical explanationsâ for understanding neural networks
- Methods for implementing multilayer neural networks from scratch, using an easy-to-understand object-oriented framework
- Working implementations and clear-cut explanations of convolutional and recurrent neural networks
- Implementation of these neural network concepts using the popular PyTorch framework
"Synopsis" may belong to another edition of this title.
About the Author
"About the title" may belong to another edition of this title.
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