Deep Learning with PyTorch Quick Start Guide

Deep Learning with PyTorch Quick Start Guide pdf epub mobi txt 电子书 下载 2025

David Julian is a freelance technology consultant and educator. He has worked as a consultant for government, private, and community organizations on a variety of projects, including using machine learning to detect insect outbreaks in controlled agricultural environments (Urban Ecological Systems Ltd., Bluesmart Farms), designing and implementing event management data systems (Sustainable Industry Expo, Lismore City Council), and designing multimedia interactive installations (Adelaide University). He has also written Designing Machine Learning Systems With Python for Packt Publishing and was a technical reviewer for Python Machine Learning and Hands-On Data Structures and Algorithms with Python - Second Edition, published by Packt.

出版者:Packt Publishing Limited
作者:David Julian
出品人:
页数:138
译者:
出版时间:2018-12
价格:0
装帧:Paperback
isbn号码:9781789534092
丛书系列:
图书标签:
  • python 
  • DataScience 
  •  
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PyTorch is extremely powerful and yet easy to learn. It provides advanced features, such as supporting multiprocessor, distributed, and parallel computation. This book is an excellent entry point for those wanting to explore deep learning with PyTorch to harness its power.

This book will introduce you to the PyTorch deep learning library and teach you how to train deep learning models without any hassle. We will set up the deep learning environment using PyTorch, and then train and deploy different types of deep learning models, such as CNN, RNN, and autoencoders.

You will learn how to optimize models by tuning hyperparameters and how to use PyTorch in multiprocessor and distributed environments. We will discuss long short-term memory network (LSTMs) and build a language model to predict text.

By the end of this book, you will be familiar with PyTorch's capabilities and be able to utilize the library to train your neural networks with relative ease.

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Pytorch 1.0 之后确实很方便。

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Pytorch 1.0 之后确实很方便。

评分

Pytorch 1.0 之后确实很方便。

评分

Pytorch 1.0 之后确实很方便。

评分

Pytorch 1.0 之后确实很方便。

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