Programming PyTorch for Deep Learning 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024


Programming PyTorch for Deep Learning

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Ian Pointer 作者
O'Reilly
譯者
2019-11-4 出版日期
300 頁數
USD 39.99 價格
Paperback
叢書系列
9781492045359 圖書編碼

Programming PyTorch for Deep Learning 在線電子書 圖書標籤: 機器學習  pytorch  計算機科學  計算機  人工智能  DataScience   


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Programming PyTorch for Deep Learning 在線電子書 epub 下載 mobi 下載 pdf 下載 txt 下載 2024

Programming PyTorch for Deep Learning 在線電子書 epub 下載 pdf 下載 mobi 下載 txt 下載 2024

Programming PyTorch for Deep Learning 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024



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【書.2020-02】學個pytorch.

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【書.2020-02】學個pytorch.

Programming PyTorch for Deep Learning 在線電子書 著者簡介

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.


Programming PyTorch for Deep Learning 在線電子書 著者簡介


Programming PyTorch for Deep Learning 在線電子書 pdf 下載 txt下載 epub 下載 mobi 在線電子書下載

Programming PyTorch for Deep Learning 在線電子書 圖書描述

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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