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[README](https://github.com/DjangoPeng/tensorflow-101) - [License](https://github.com/DjangoPeng/tensorflow-101) **Table of Contents** *generated with [DocToc](https://github.com/thlorenz/doctoc)* - [TensorFlow 快速入门与实战](https://github.com/DjangoPeng/tensorflow-101#tensorflow-%E5%BF%AB%E9%80%9F%E5%85%A5%E9%97%A8%E4%B8%8E%E5%AE%9E%E6%88%98) - [课程列表](https://github.com/DjangoPeng/tensorflow-101#%E8%AF%BE%E7%A8%8B%E5%88%97%E8%A1%A8) - [第一部分：TensorFlow初印象](https://github.com/DjangoPeng/tensorflow-101#%E7%AC%AC%E4%B8%80%E9%83%A8%E5%88%86tensorflow%E5%88%9D%E5%8D%B0%E8%B1%A1) - [第二部分：TensorFlow初接触](https://github.com/DjangoPeng/tensorflow-101#%E7%AC%AC%E4%BA%8C%E9%83%A8%E5%88%86tensorflow%E5%88%9D%E6%8E%A5%E8%A7%A6) - [第三部分：TensorFlow基础概念解析](https://github.com/DjangoPeng/tensorflow-101#%E7%AC%AC%E4%B8%89%E9%83%A8%E5%88%86tensorflow%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5%E8%A7%A3%E6%9E%90) - [第四部分：实战TensorFlow房价预测](https://github.com/DjangoPeng/tensorflow-101#%E7%AC%AC%E5%9B%9B%E9%83%A8%E5%88%86%E5%AE%9E%E6%88%98tensorflow%E6%88%BF%E4%BB%B7%E9%A2%84%E6%B5%8B) - [第五部分：实战TensorFlow手写体数字识别](https://github.com/DjangoPeng/tensorflow-101#%E7%AC%AC%E4%BA%94%E9%83%A8%E5%88%86%E5%AE%9E%E6%88%98tensorflow%E6%89%8B%E5%86%99%E4%BD%93%E6%95%B0%E5%AD%97%E8%AF%86%E5%88%AB) - [第六部分：实战TensorFlow验证码识别](https://github.com/DjangoPeng/tensorflow-101#%E7%AC%AC%E5%85%AD%E9%83%A8%E5%88%86%E5%AE%9E%E6%88%98tensorflow%E9%AA%8C%E8%AF%81%E7%A0%81%E8%AF%86%E5%88%AB) - [第七部分：实战TensorFlow人脸识别](https://github.com/DjangoPeng/tensorflow-101#%E7%AC%AC%E4%B8%83%E9%83%A8%E5%88%86%E5%AE%9E%E6%88%98tensorflow%E4%BA%BA%E8%84%B8%E8%AF%86%E5%88%AB) - [第八部分：TensorFlow社区参与指南](https://github.com/DjangoPeng/tensorflow-101#%E7%AC%AC%E5%85%AB%E9%83%A8%E5%88%86tensorflow%E7%A4%BE%E5%8C%BA%E5%8F%82%E4%B8%8E%E6%8C%87%E5%8D%97) - [问题答疑](https://github.com/DjangoPeng/tensorflow-101#%E9%97%AE%E9%A2%98%E7%AD%94%E7%96%91) - [1\. Windows 上安装 TensorFlow 流程](https://github.com/DjangoPeng/tensorflow-101#1-windows-%E4%B8%8A%E5%AE%89%E8%A3%85-tensorflow-%E6%B5%81%E7%A8%8B) - [2\. 学这个课程需要什么样的基础？](https://github.com/DjangoPeng/tensorflow-101#2-%E5%AD%A6%E8%BF%99%E4%B8%AA%E8%AF%BE%E7%A8%8B%E9%9C%80%E8%A6%81%E4%BB%80%E4%B9%88%E6%A0%B7%E7%9A%84%E5%9F%BA%E7%A1%80) # TensorFlow 快速入门与实战 [](https://camo.githubusercontent.com/aef0d88a842c0f16a3c9364e7f0383e792a3820273094aae99c8a84fd393d58a/68747470733a2f2f70696e73686976312e6f73732d636e2d68616e677a686f752e616c6979756e63732e636f6d2f61692f636f757273655f706f737465725f312e6a706567) [](https://camo.githubusercontent.com/ba60681c0a4acb1c88534e0d4559706f150a1c69d0bb0cfe876b95715e9938a6/68747470733a2f2f70696e73686976312e6f73732d636e2d68616e677a686f752e616c6979756e63732e636f6d2f61692f636f757273655f706f737465722e6a7067) ## 交流讨论群 [](https://camo.githubusercontent.com/7723619a1c80484c7a1be25c8fa9e465ac612b62eca885683cecf04a4be89949/68747470733a2f2f70696e73686976312e6f73732d636e2d68616e677a686f752e616c6979756e63732e636f6d2f61692f71722e706e67) ## 课程列表 #### 第一部分：TensorFlow初印象 [课件](https://github.com/DjangoPeng/tensorflow-101/blob/master/beginners/slides/1-TensorFlow%E5%88%9D%E5%8D%B0%E8%B1%A1.pdf) #### 第二部分：TensorFlow初接触 [课件](https://github.com/DjangoPeng/tensorflow-101/blob/master/beginners/slides/2-TensorFlow%E5%88%9D%E6%8E%A5%E8%A7%A6.pdf) \| [代码](https://github.com/DjangoPeng/tensorflow-101/blob/master/beginners/notebook-examples/chapter-2) #### 第三部分：TensorFlow基础概念解析 [课件](https://github.com/DjangoPeng/tensorflow-101/blob/master/beginners/slides/3-TensorFlow%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5%E8%A7%A3%E6%9E%90.pdf) \| [代码](https://github.com/DjangoPeng/tensorflow-101/blob/master/beginners/notebook-examples/chapter-3) #### 第四部分：实战TensorFlow房价预测 [课件](https://github.com/DjangoPeng/tensorflow-101/blob/master/beginners/slides/4-%E5%AE%9E%E6%88%98TensorFlow%E6%88%BF%E4%BB%B7%E9%A2%84%E6%B5%8B.pdf) \| [代码](https://github.com/DjangoPeng/tensorflow-101/blob/master/beginners/notebook-examples/chapter-4) #### 第五部分：实战TensorFlow手写体数字识别 [课件](https://github.com/DjangoPeng/tensorflow-101/blob/master/beginners/slides/5-%E5%AE%9E%E6%88%98TensorFlow%E6%89%8B%E5%86%99%E4%BD%93%E6%95%B0%E5%AD%97%E8%AF%86%E5%88%AB.pdf) \| [代码](https://github.com/DjangoPeng/tensorflow-101/blob/master/beginners/notebook-examples/chapter-5) #### 第六部分：实战TensorFlow验证码识别 [课件](https://github.com/DjangoPeng/tensorflow-101/blob/master/beginners/slides/6-%E5%AE%9E%E6%88%98TensorFlow%E9%AA%8C%E8%AF%81%E7%A0%81%E8%AF%86%E5%88%AB.pdf) \| [代码](https://github.com/DjangoPeng/tensorflow-101/blob/master/beginners/notebook-examples/chapter-6) #### 第七部分：实战TensorFlow人脸识别 [课件](https://github.com/DjangoPeng/tensorflow-101/blob/master/beginners/slides/7-%E5%AE%9E%E6%88%98TensorFlow%E4%BA%BA%E8%84%B8%E8%AF%86%E5%88%AB.pdf) \| [代码](https://github.com/DjangoPeng/tensorflow-101/blob/master/beginners/notebook-examples/chapter-7) #### 第八部分：TensorFlow社区参与指南 [课件](https://github.com/DjangoPeng/tensorflow-101/blob/master/beginners/slides/8-TensorFlow%E7%A4%BE%E5%8C%BA%E5%8F%82%E4%B8%8E%E6%8C%87%E5%8D%97.pdf) ## 问题答疑 **我将极客时间上多次提到的问题整理在此，希望可以解答有同样问题的朋友。** #### 1\. Windows 上安装 TensorFlow 流程 对于有英文基础的朋友，建议直接阅读官网[安装教程](https://www.tensorflow.org/install/pip?lang=python3)。本答案翻译自 TensorFlow 官网。 系统环境要求： - Windows 7（64位) 以上版本 - Python 3.4, 3.5 或 3.6 Windows 上安装 TensorFlow 步骤： 1. 安装 Python 开发环境 检查系统是否已安装 Python 开发环境。如果已安装，则跳过该步骤。 ``` python3 --version pip3 --version virtualenv --version ``` > 1. 独立安装 Microsoft Visual C++ 2015 Redistributable Update 3 或安装完整的 Visual Studio 2015： > > - 进入 Visual Studio [下载页](https://visualstudio.microsoft.com/vs/older-downloads/) > - 选择 **Redistributables and Build Tools** > - 下载和安装 Microsoft Visual C++ 2015 Redistributable Update 3 > 1. 安装 Windows 上 [64位的 Python 3 发布版](https://www.python.org/downloads/windows/) > 1. 安装 **pip** 和 **virtualenv** > ``` > pip3 install -U pip virtualenv > ``` 1. 创建 Python 虚拟环境 ``` virtualenv --system-site-packages -p python3 ./venv .\venv\Scripts\activate pip install --upgrade pip pip list # 展示 venv 中已安装的软件包 deactivate # 使用完 TensorFlow 后，方可推出 venv 虚拟环境 ``` 1. 安装 TensorFlow pip 包 ``` pip install --upgrade tensorflow python -c "import tensorflow as tf; tf.enable_eager_execution(); print(tf.reduce_sum(tf.random_normal([1000, 1000])))" ``` #### 2\. 学这个课程需要什么样的基础？ [](https://github.com/DjangoPeng/tensorflow-101/blob/master/beginners/images/knowledge-graph-0.jpg) [](https://github.com/DjangoPeng/tensorflow-101/blob/master/beginners/images/knowledge-graph-1.jpg) ## About 《TensorFlow 快速入门与实战》和《TensorFlow 2 项目进阶实战》课程代码与课件 [time.geekbang.org/course/intro/100053201](https://time.geekbang.org/course/intro/100053201 "https://time.geekbang.org/course/intro/100053201") ### Topics [python](https://github.com/topics/python "Topic: python") [machine-learning](https://github.com/topics/machine-learning "Topic: machine-learning") [tensorflow](https://github.com/topics/tensorflow "Topic: tensorflow") ### Resources [Readme](https://github.com/DjangoPeng/tensorflow-101#readme-ov-file) ### License [View license](https://github.com/DjangoPeng/tensorflow-101#License-1-ov-file) ### Uh oh\! 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