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Synopsis
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
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
Seth Weidman is a data scientist who has applied and taught machine learning concepts for several years. He started out as the first data scientist at Trunk Club, where he built lead scoring models and recommender systems, and currently works at Facebook, where he builds machine learning models for their infrastructure team. In between he taught data science and machine learning for the bootcamps and on the corporate training team at Metis. He is passionate about explaining complex concepts simply, striving to find the simplicity on the other side of complexity.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Deep Learning from Scratch: Building with Python from First Principles
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O'Reilly Media, 2019
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Deep Learning from Scratch
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Paperback. Etat : New. 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 models-accompanied by working code examples and mathematical explanations-for understanding neural networksMethods for implementing multilayer neural networks from scratch, using an easy-to-understand object-oriented frameworkWorking implementations and clear-cut explanations of convolutional and recurrent neural networksImplementation of these neural network concepts using the popular PyTorch framework. N° de réf. du vendeur LU-9781492041412
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Deep Learning from Scratch: Building with Python from First Principles
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Deep Learning from Scratch: Building with Python from First Principles (Paperback or Softback)
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ISBN 13 : 9781492041412
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Deep Learning from Scratch
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Paperback. Etat : New. 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 models-accompanied by working code examples and mathematical explanations-for understanding neural networksMethods for implementing multilayer neural networks from scratch, using an easy-to-understand object-oriented frameworkWorking implementations and clear-cut explanations of convolutional and recurrent neural networksImplementation of these neural network concepts using the popular PyTorch framework. N° de réf. du vendeur LU-9781492041412
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Deep Learning from Scratch: Building with Python from First Principles
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Deep Learning from Scratch: Building with Python from First Principles
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ISBN 10 : 1492041416
ISBN 13 : 9781492041412
Neuf
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