出版社: Manning Publications
出版年: 2017-10-31
页数: 350
定价: USD 49.99
装帧: Paperback
ISBN: 9781617294433
内容简介 · · · · · ·
Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-lang...
Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects.
作者简介 · · · · · ·
François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences i...
François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others.
目录 · · · · · ·
1.What is deep learning?
2.Before we begin: the mathematical building blocks of neural networks
3.Getting started with neural networks
4.Fundamentals of machine learning
PART 2 - DEEP LEARNING IN PRACTICE
· · · · · · (更多)
1.What is deep learning?
2.Before we begin: the mathematical building blocks of neural networks
3.Getting started with neural networks
4.Fundamentals of machine learning
PART 2 - DEEP LEARNING IN PRACTICE
5.Deep learning for computer vision
6.Deep learning for text and sequences
7.Advanced deep-learning best practices
8.Generative deep learning
9.Conclusions
appendix A - Installing Keras and its dependencies on Ubuntu
appendix B - Running Jupyter notebooks on an EC2 GPU instance
· · · · · · (收起)
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Deep Learning with Python的书评 · · · · · · ( 全部 13 条 )
写给自己的深度学习科普
这篇书评可能有关键情节透露
读这本书的初衷的确是好奇。这两年深度学习大热,但是深度学习具体是个什么样的算法,适用于什么样的情景,和机器学习的关系是怎么样的,我完全不知,所以读完机器学习那本书,就跑过来读了这本,给自己科普一下什么是深度学习。 而读这本书的确是选对了。 首先提一下作者:弗... (展开)最容易入门的深度学习基础书
哪里有大神的个人翻译版呢?
Python深度学习
《Python深度学习(第2版)》:深度学习之旅的必备指南
这篇书评可能有关键情节透露
《Python深度学习(第2版)》:深度学习之旅的必备指南 由于深度学习领域的技术发展非常迅速,建议读者在阅读这些书籍的同时,也要关注最新的技术动态和研究成果,以便及时了解和掌握新的技术和方法。 当我们提及深度学习,许多人首先想到的是复杂的概念、高深的数学和令人望而... (展开)> 更多书评 13篇
论坛 · · · · · ·
《Deep Learning with Python》众筹 | 来自GuokLiu | 14 回应 | 2018-09-05 02:44:27 |
Are you overfitting? | 来自lvs | 2018-07-26 01:21:25 | |
Feature engineering | 来自lvs | 2018-07-18 14:45:59 | |
Engineering orientated? | 来自lvs | 2018-07-18 14:08:32 |
这本书的其他版本 · · · · · · ( 全部7 )
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人民邮电出版社 (2018)9.5分 913人读过
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人民邮电出版社 (2022)9.4分 62人读过
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Manning Publications (2021)9.5分 26人读过
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マイナビ出版 (2018)暂无评分
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订阅关于Deep Learning with Python的评论:
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1 有用 beren 2018-01-15 21:15:20
Keras作者的书,有些很有意思的例子,讲得不深,更像是Keras的代码示例,挺实用的,看完基本可以上手写了,里面套来解决各种常见问题的代码模板几乎都有。
2 有用 机动美少年高興 2019-06-01 12:54:04
语言平实,举例精妙,第 9 章的展望是真知灼见。但同时挑几个毛病:1) convolution 讲得不算太清楚;2) LSTM 和 GRU 则是直接放弃了详细叙述…… 3) Depthwise Separable Convolution 讲得不算太清楚,请配合阅读 https://eli.thegreenplace.net/2018/depthwise-separable-convolutions... 语言平实,举例精妙,第 9 章的展望是真知灼见。但同时挑几个毛病:1) convolution 讲得不算太清楚;2) LSTM 和 GRU 则是直接放弃了详细叙述…… 3) Depthwise Separable Convolution 讲得不算太清楚,请配合阅读 https://eli.thegreenplace.net/2018/depthwise-separable-convolutions-for-machine-learning;4) Deep Dream 没看懂,不如看这个 https://www.youtube.com/watch?v=BsSmBPmPeYQ (展开)
0 有用 清風明月 2022-09-26 20:53:09 日本
虽然第二版有一大部分不同的内容,并且更贴近于最新的实用。然而第一版最好也要反复的看,毕竟是一本相当经典的入门书!!!
0 有用 all the fish 2018-05-05 19:54:55
intro
0 有用 知更子 2020-09-30 23:03:59
光看一遍跑完代码感觉还是啥都不会。
0 有用 清風明月 2022-09-26 20:53:09 日本
虽然第二版有一大部分不同的内容,并且更贴近于最新的实用。然而第一版最好也要反复的看,毕竟是一本相当经典的入门书!!!
0 有用 欧阳映月 2022-04-14 02:12:41
非常实用的入门书,有些tensorflow的使用方法可能过时了,但是不妨碍学习。
0 有用 有时雨 2022-03-08 01:02:42
My first machine learning book🤧常阅常新
0 有用 喀喀喀 2022-01-18 20:50:25
在作者写这本书的时候,无出其右者。。。 强烈推荐第二版 - 比第一版还要好。
0 有用 chch 2021-12-17 06:09:51
一口气读了差不多四章,欲罢不能!这次读完,以后肯定要回头再读