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Relph1119 / Deeplearning With Tensorflow Notes

Licence: gpl-3.0
龙曲良《TensorFlow深度学习》学习笔记及代码,采用TensorFlow2.0.0版本

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TensorFlow深度学习练习代码

  龙龙(龙曲良)老师的《TensorFlow深度学习》是TensorFlow2.0入门教材之一。
  本书共15章,大体上可分为4个部份:第1-3章为第1部分,主要介绍人工智能的初步认知,并引出相关问题;第4-5章为第2部分,主要介绍TensorFlow相关基础,为后续算法实现铺垫;第6-9章为第3部分,主要介绍神经网络的核心理论和共性知识,让读者理解深度学习的本质;第10-15章为模型算法应用部分,主要介绍常见的算法与模型,让读者能够学有所用。
  申明: 所有的代码都来源于《TensorFlow深度学习》,github地址:https://github.com/dragen1860/Deep-Learning-with-TensorFlow-book。

使用说明

  1. 本练习代码是搭配龙龙老师的《TensorFlow深度学习》一书。
  2. 关于本笔记中的练习代码,已经消缺了书中代码的错误,可以很方便地执行程序。
  3. 关于书中的很多图,已经写好了生成数据图的代码,在对应的目录下也有数据图。
  4. 关于书中很多用jupyter notebook写的代码示例,也在对应的目录下有对应章节的ipynb文档。
  5. 关于python包的版本问题,请详见requirements.txt文件,笔者采用的tensorflow-gpu==2.0.0,可以使用cpu版本,但是运行会特别慢。
  6. keras模型与数据下载地址:链接:https://pan.baidu.com/s/1Rt6KYWUAQ8MWKY9UVVDtmQ 提取码:wedp
  7. 相关数据集和gym包,百度网盘的下载地址:链接:https://pan.baidu.com/s/1fZ748Xz3WrgQnIaxGsrZLQ,提取码:ea6u

  使用windows平台的tensorflow,将keras中的datasets和models放入到C:\Users\{pcUserName}\.keras路径下,其他的数据包,在对应的练习代码中有说明。

选用的《TensorFlow深度学习》版本

书名:TensorFlow深度学习
作者:龙龙老师
版次:2019年12月05日测试版第2版

电子书(带书签-无水印版)的百度网盘地址:链接:https://pan.baidu.com/s/1CPXZSrqVTJWHc3cYXIYjNg,提取码:mrhw

主要贡献者(按首字母排名)

@胡锐锋-天国之影-Relph

总结

  本书总共用了16天(2020年2月14日-2020年3月1日)阅读完,对TensorFlow和Keras的使用有很大的收获,其中第11、13章和第15章的scratch训练,由于电脑的显卡不好,不能完成练习,但其他章节的练习均已完成。

注意: 如果出现以下这个错误,说明显卡的显存太低,可以将代码和数据集放到Google Colab上面执行。

tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[500,500,500] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc [Op:Sub] name: sub/

LICENSE

GNU General Public License v3.0

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