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30天掌握Tensorflow2.1 Jupyter Notebook 版

Jupyter Notebook 100.00%

eat_tensorflow2_in_30_days_ipynb's Introduction

eat_tensorflow2_in_30_days_ipynb

eat_tensorflow2_in_30_days_ipynb为《30天吃掉那只TensorFlow2.0 》Jupyter Notebook 运行版本。

感谢原作者lyhue1991提供的教程。

Convert to English version.

1、章节目录 ⏰

点击对应蓝色标题即可进入该章节。

日期 学习内容 内容难度 预计学习时间 更新状态
  一、TensorFlow的建模流程 ⭐️ 0 hour
day1 1-1 结构化数据建模流程范例 ⭐️⭐️⭐️ 1 hour
day2 1-2 图片数据建模流程范例 ⭐️⭐️⭐️⭐️ 2 hour
day3 1-3 文本数据建模流程范例 ⭐️⭐️⭐️⭐️⭐️ 2 hour
day4 1-4 时间序列数据建模流程范例 ⭐️⭐️⭐️⭐️⭐️ 2 hour
  二、TensorFlow的核心概念 ⭐️ 0 hour
day5 2-1 张量数据结构 ⭐️⭐️⭐️⭐️ 1 hour
day6 2-2 三种计算图 ⭐️⭐️⭐️⭐️⭐️ 2 hour
day7 2-3 自动微分机制 ⭐️⭐️⭐️ 1 hour
  三、TensorFlow的层次结构 ⭐️ 0 hour
day8 3-1 低阶API示范 ⭐️⭐️ 0.5 hour
day9 3-2 中阶API示范 ⭐️⭐️⭐️ 0.5 hour
day10 3-3 高阶API示范 ⭐️⭐️⭐️ 0.5 hour
  四、TensorFlow的低阶API ⭐️ 0 hour
day11 4-1 张量的结构操作 ⭐️⭐️⭐️⭐️⭐️ 2 hour
day12 4-2 张量的数学运算 ⭐️⭐️⭐️⭐️ 1 hour
day13 4-3 AutoGraph的使用规范 ⭐️⭐️⭐️ 0.5 hour
day14 4-4 AutoGraph的机制原理 ⭐️⭐️⭐️⭐️⭐️ 2 hour
day15 4-5 AutoGraph和tf.Module ⭐️⭐️⭐️⭐️ 1 hour
  五、TensorFlow的中阶API ⭐️ 0 hour
day16 5-1 数据管道Dataset ⭐️⭐️⭐️⭐️⭐️ 2 hour
day17 5-2 特征列feature_column ⭐️⭐️⭐️⭐️ 1 hour
day18 5-3 激活函数activation ⭐️⭐️⭐️ 0.5 hour
day19 5-4 模型层layers ⭐️⭐️⭐️ 1 hour
day20 5-5 损失函数losses ⭐️⭐️⭐️ 1 hour
day21 5-6 评估指标metrics ⭐️⭐️⭐️ 1 hour
day22 5-7 优化器optimizers ⭐️⭐️⭐️ 0.5 hour
day23 5-8 回调函数callbacks ⭐️⭐️⭐️⭐️ 1 hour
  六、TensorFlow的高阶API ⭐️ 0 hour
day24 6-1 构建模型的3种方法 ⭐️⭐️⭐️ 1 hour
day25 6-2 训练模型的3种方法 ⭐️⭐️⭐️⭐️ 1 hour
day26 6-3 使用单GPU训练模型 ⭐️⭐️ 0.5 hour
day27 6-4 使用多GPU训练模型 ⭐️⭐️ 0.5 hour
day28 6-5 使用TPU训练模型 ⭐️⭐️ 0.5 hour
day29 6-6 使用tensorflow-serving部署模型 ⭐️⭐️⭐️⭐️ 1 hour
day29 6-6-1 使用tensorflow-serving-colab部署模型 ⭐️⭐️⭐️⭐️ 1 hour
day30 6-7 使用spark-scala调用tensorflow模型 ⭐️⭐️⭐️⭐️⭐️ 2 hour

2、运行环境

本书全部源码在jupyter中编写测试通过,建议通过git克隆到本地,并在jupyter中交互式运行学习。

#建议在终端上安装最新版本tensorflow 测试此教程中的代码
pip install -i https://pypi.tuna.tsinghua.edu.cn/simple  -U tensorflow
import tensorflow as tf

#注:全部代码在tensorflow 2.1版本测试通过
tf.print("tensorflow version:",tf.__version__)
tensorflow version: 2.1.0

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