作者简介

Shanging Cai, Stanley Bileschi and Eric D. Nielsen are software engineers with experience on the Google Brain team, and were crucial to the development of the high-level API of TensorFlow.js. This book is based in part on the classic, Deep Learning with Python by François Chollet.

内容简介

In Deep Learning with JavaScript, you’ll learn to use TensorFlow.js to build deep learning models that run directly in the browser. This fast-paced book, written by Google engineers, is practical, engaging, and easy to follow. Through diverse examples featuring text analysis, speech processing, image recognition, and self-learning game AI, you’ll master all the basics of deep learning and explore advanced concepts, like retraining existing models for transfer learning and image generation.

what's inside

Image and language processing in the browser

Tuning ML models with client-side data

Text and image creation with generative deep learning

Source code samples to test and modify


Shanging Cai, Stanley Bileschi and Eric D. Nielsen are software engineers with experience on the Google Brain team, and were crucial to the development of the high-level API of TensorFlow.js. This book is based in part on the classic, Deep Learning with Python by François Chollet.

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豆瓣评论

  • 奶茶加糖不要钱
    2020年第一个限时读书目标,2.10来还愿==================================目前读完第9章,本书可以说是《Python深度学习》的JavaScript语言实现姊妹篇,撰写思路很类似。书中选取的例子来自tfjs-examples仓库,每章会针对其中一个例子涉及的topic进行说明。第9章的seq2seq的相关内容基本是懵着看完的,突然结尾隐约有一种作者写着写着就let it go的感觉。前8章还是比较不错的,暂且给4星。============20200225终于读完了,4星好评。希望有时间再看一遍part 3,把稀里糊涂看过去的部分弄清楚。还有出版社引进的时候翻译好一点。02-25

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