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Deep learning with Python : learn be...

Ketkar, Nikhil.

Deep learning with Python : learn best practices of deep learning models with PyTorch

紀錄類型:	書目-語言資料,印刷品 : 單行本
副題名:	learn best practices of deep learning models with PyTorch
作者:	KetkarNikhil.,
其他作者:	MoolayilJojo.,
出版地:	[Berkeley, CA]
出版者:	Apress;
出版年:	c2021.
版本:	2nd ed.
面頁冊數:	xvii, 306 p.ill. : 24 cm.;
標題:	Machine learning. -
標題:	Python (Computer program language) -
標題:	Data mining. -
附註:	Includes index.
摘要註:	Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and practice. This updated edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and practical know-how with PyTorch, a platform developed by Facebook's Artificial Intelligence Research Group. You'll start with a perspective on how and why deep learning with PyTorch has emerged as an path-breaking framework with a set of tools and techniques to solve real-world problems. Next, the book will ground you with the mathematical fundamentals of linear algebra, vector calculus, probability and optimization. Having established this foundation, you'll move on to key components and functionality of PyTorch including layers, loss functions and optimization algorithms. You'll also gain an understanding of Graphical Processing Unit (GPU) based computation, which is essential for training deep learning models. All the key architectures in deep learning are covered, including feedforward networks, convolution neural networks, recurrent neural networks, long short-term memory networks, autoencoders and generative adversarial networks. Backed by a number of tricks of the trade for training and optimizing deep learning models, this edition of Deep Learning with Python explains the best practices in taking these models to production with PyTorch. You will: Review machine learning fundamentals such as overfitting, underfitting, and regularization. Understand deep learning fundamentals such as feed-forward networks, convolution neural networks, recurrent neural networks, automatic differentiation, and stochastic gradient descent. Apply in-depth linear algebra with PyTorch Explore PyTorch fundamentals and its building blocks Work with tuning and optimizing models
ISBN:	9781484253632
內容註:	Chapter 1 - Introduction Deep Learning Chapter 2 - Introduction to PyTorch Chapter 3- Feed Forward Networks Chapter 4 - Automatic Differentiation in Deep Learning Chapter 5 - Training Deep Neural Networks Chapter 6 - Convolutional Neural Networks Chapter 7 - Recurrent Neural Networks Chapter 8 - Recent advances in Deep Learning.

Deep learning with Python : learn best practices of deep learning models with PyTorch
Ketkar, Nikhil.

Deep learning with Python : learn best practices of deep learning models with PyTorch / Nikhil Ketkar, Jojo Moolayil. - 2nd ed.. - [Berkeley, CA] : Apress, c2021.. - xvii, 306 p. ; ill. ; 24 cm..
Chapter 1 - Introduction Deep Learning.
Includes index..
ISBN 9781484253632
Machine learning.Python (Computer program language)Data mining.

Moolayil, Jojo.

Deep learning with Python : learn best practices of deep learning models with PyTorch
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