Programming PyTorch for Deep Learning 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024


Programming PyTorch for Deep Learning

简体网页||繁体网页
Ian Pointer 作者
O'Reilly
译者
2019-11-4 出版日期
300 页数
USD 39.99 价格
Paperback
丛书系列
9781492045359 图书编码

Programming PyTorch for Deep Learning 在线电子书 图书标签: 机器学习  pytorch  计算机科学  计算机  人工智能  DataScience   


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发表于2024-12-26


Programming PyTorch for Deep Learning 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Programming PyTorch for Deep Learning 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Programming PyTorch for Deep Learning 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024



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【书.2020-02】学个pytorch.

Programming PyTorch for Deep Learning 在线电子书 著者简介

Currently Ian is the Director of Partner Engineering at a company called Kogentix that specializes in Machine Learning solutions (including Deep Learning techniques), with multiple Fortune 100 clients. Prior to that, he worked for many years at an early Big Data startup called Mammoth Data, cutting his teeth on Apache Hadoop and Apache Spark. He emigrated to the US from the UK in 2011 and became an American citizen in 2017.


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Programming PyTorch for Deep Learning 在线电子书 pdf 下载 txt下载 epub 下载 mobi 在线电子书下载

Programming PyTorch for Deep Learning 在线电子书 图书描述

Deep learning is changing everything. This machine-learning method has already surpassed traditional computer vision techniques, and the same is happening with NLP. If you're looking to bring deep learning into your domain, this practical book will bring you up to speed on key concepts using Facebook's PyTorch framework.

Once author Ian Pointer helps you set up PyTorch on a cloud-based environment, you'll learn how use the framework to create neural architectures for performing operations on images, sound, text, and other types of data. By the end of the book, you'll be able to create neural networks and train them on multiple types of data.

Learn how to deploy deep learning models to production

Explore PyTorch use cases in companies other than Facebook

Learn how to apply transfer learning to images

Apply cutting-edge NLP techniques using a model trained on Wikipedia

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