# TensorFlow2.0-Examples

**Repository Path**: se7enXF/TensorFlow2.0-Examples

## Basic Information

- **Project Name**: TensorFlow2.0-Examples
- **Description**: Fork from github
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2019-07-22
- **Last Updated**: 2022-06-12

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README


# Tensorflow2.0 Examples

> "Talk is cheap, show me the code." <br>
>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;--------- Linus Torvalds

This tutorial was designed for easily diving into TensorFlow2.0.  it includes both notebooks and source codes with explanation. It will be continuously updated ! 🐍🐍🐍🐍🐍🐍

#### 1 - Introduction
- **Hello World** ([notebook](https://nbviewer.jupyter.org/github/YunYang1994/tensorflow2.0-examples/blob/master/1-Introduction/helloworld.ipynb)) ([code](1-Introduction/helloworld.py)). Very simple example to learn how to print "hello world" using TensorFlow.
- **Variable** ([notebook](https://nbviewer.jupyter.org/github/YunYang1994/tensorflow2.0-examples/blob/master/1-Introduction/variable.ipynb)) ([code](1-Introduction/variable.py)). Learn to use variable in tensorflow.
- **Basical operation** ([notebook](https://nbviewer.jupyter.org/github/YunYang1994/tensorflow2.0-examples/blob/master/1-Introduction/basic_operations.ipynb)) ([code](1-Introduction/basic_operations.py)). A simple example that covers TensorFlow basic operations.
- **Activation** ([notebook](https://nbviewer.jupyter.org/github/YunYang1994/tensorflow2.0-examples/blob/master/1-Introduction/activation.ipynb)) ([code](1-Introduction/activation.py)). Start to know some activation functions in tensorflow.
- **GradientTape** ([notebook](https://nbviewer.jupyter.org/github/YunYang1994/tensorflow2.0-examples/blob/master/1-Introduction/GradientTape.ipynb)) ([code](1-Introduction/GradientTape.py)). Introduce a key technique for automatic differentiation

#### 2 - Basical Models
- **Linear Regression** ([notebook](https://nbviewer.jupyter.org/github/YunYang1994/tensorflow2.0-examples/blob/master/2-Basical_Models/Linear_Regression.ipynb)) ([code](2-Basical_Models/Linear_Regression.py)). Implement a Linear Regression with TensorFlow.
- **Logistic Regression** ([notebook](https://nbviewer.jupyter.org/github/YunYang1994/tensorflow2.0-examples/blob/master/2-Basical_Models/Logistic_Regression.ipynb)) ([code](2-Basical_Models/Logistic_Regression.py)). Implement a Logistic Regression with TensorFlow.
- **Multilayer Perceptron Layer** ([notebook](https://nbviewer.jupyter.org/github/YunYang1994/tensorflow2.0-examples/blob/master/2-Basical_Models/Multilayer_Perceptron.ipynb)) ([code](2-Basical_Models/Multilayer_Perceptron.py)). Implement Multi-Layer Perceptron Model with TensorFlow.

#### 3 - Image Classification

- **VGG16** ([notebook](https://github.com/YunYang1994/TensorFlow2.0-Examples/tree/master/3-Image_Classification/vgg16)) ([code](https://github.com/YunYang1994/TensorFlow2.0-Examples/tree/master/3-Image_Classification/vgg16/vgg16.py))([paper](https://arxiv.org/pdf/1409.1556.pdf)). VGG16: Very Deep Convolutional Networks for Large-Scale Image Recognition 

#### 4 - Object Detection

- **YOLOv3** ([notebook](https://github.com/YunYang1994/TensorFlow2.0-Examples/tree/master/4-Object_Detection/YOLOV3)) ([code](https://github.com/YunYang1994/TensorFlow2.0-Examples/tree/master/4-Object_Detection/YOLOV3/core/yolov3.py))([paper](https://arxiv.org/pdf/1804.02767.pdf)). YOLOv3: An Incremental Improvement.🔥🔥🔥🔥🔥
- **RPN** ([notebook](https://github.com/YunYang1994/TensorFlow2.0-Examples/tree/master/4-Object_Detection/RPN)) ([code](https://github.com/YunYang1994/TensorFlow2.0-Examples/tree/master/4-Object_Detection/RPN)). RPN: RegionProposal Network, Backbone of [Faster R-CNN](https://arxiv.org/pdf/1506.01497.pdf) 🔥🔥🔥

#### 5 - Generative Adversarial Networks
- **DCGAN** ([notebook](https://nbviewer.jupyter.org/github/YunYang1994/tensorflow2.0-examples/blob/master/5-Generative_Adversarial_Networks/dcgan.ipynb)) ([code](5-Generative_Adversarial_Networks/dcgan.py))([paper](https://arxiv.org/pdf/1511.06434.pdf)).  Deep Convolutional Generative Adversarial Network.
- **Pix2Pix** ([notebook](https://nbviewer.jupyter.org/github/YunYang1994/tensorflow2.0-examples/blob/master/5-Generative_Adversarial_Networks/Pix2Pix.ipynb)) ([code](5-Generative_Adversarial_Networks/Pix2Pix.py))([paper](https://arxiv.org/pdf/1611.07004.pdf)).  Image-to-Image Translation with Conditional Adversarial Networks.

#### 6 - Reinforcement Learning

- **DQN** ([notebook](6-Reinforcement_Learning/YOLOV2.ipynb)) ([code](6-Reinforcement_Learning/YOLOV2.py)). deep Q-network (DQN).

#### 7 - Utilities