# tensorflow2-docs-zh

**Repository Path**: fundata/tensorflow2-docs-zh

## Basic Information

- **Project Name**: tensorflow2-docs-zh
- **Description**: TF2.0 / TensorFlow 2.0 / TensorFlow2.0 官方文档中文版
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 1
- **Created**: 2022-08-15
- **Last Updated**: 2022-08-15

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# TensorFlow 2 / 2.0 官方文档中文版

![TensorFlow 2.0](tf2doc/tf.jpg)

## 相关链接

- [一篇文章入门 Python](https://geektutu.com/post/quick-python.html)
- [机器学习笔试面试题](https://geektutu.com/post/qa-ml.html)，[Github](https://github.com/geektutu/interview-questions)
- [TensorFlow 2.0 中文文档](https://geektutu.com/post/tf2doc.html)，[Github](https://github.com/geektutu/tensorflow2-docs-zh)
- [TensorFlow 2.0 图像识别&强化学习实战](https://geektutu.com/post/tensorflow2-mnist-cnn.html)，[Github](https://github.com/geektutu/tensorflow-tutorial-samples)
## 目录(持续更新)

### 基础 - 机器学习基础 ML basics

1. [图像分类 Classify images](https://geektutu.com/post/tf2doc-ml-basic-image.html)
2. [文本分类 Classify text](https://geektutu.com/post/tf2doc-ml-basic-text.html)
3. [结构化数据分类 Classify structured data](https://geektutu.com/post/tf2doc-ml-basic-structured-data.html)
4. [回归 Regression](https://geektutu.com/post/tf2doc-ml-basic-regression.html)
5. [过拟合与欠拟合 Overfitting and underfitting](https://geektutu.com/post/tf2doc-ml-basic-overfit.html)
6. [保存和恢复模型 Save and restore models](https://geektutu.com/post/tf2doc-ml-basic-save-model.html)

### 基础 - 图像分类

1. [卷积神经网络 Convolutional Neural Networks](https://geektutu.com/post/tf2doc-cnn-cifar10.html)
2. [使用TFHub进行迁移学习 TensorFlow Hub with Keras](https://geektutu.com/post/tf2doc-tfhub-image-tl.html)
3. 使用预训练CNN进行迁移学习 Transfer Learning Using Pretrained ConvNets

### 基础 - 文本分类

1. [使用RNN对文本分类进行分类 Text classification with an RNN](https://geektutu.com/post/tf2doc-rnn-lstm-text.html)

### 进阶 - 自定义

1. 张量和操作 Tensors and operations
2. 自定义层 Custom layers
3. 自动微分 Automatic differentiation
4. 自定义训练：攻略 Custom training：walkthrough
5. 动态图机制 TF function and AutoGraph