Tensorflow2.0 Examples

"Talk is cheap, show me the code."
                                                                     --------- 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) (code). Very simple example to learn how to print "hello world" using TensorFlow.
• Variable (notebook) (code). Learn to use variable in tensorflow.
• Basical operation (notebook) (code). A simple example that covers TensorFlow basic operations.
• Activation (notebook) (code). Start to know some activation functions in tensorflow.
• GradientTape (notebook) (code). Introduce a key technique for automatic differentiation

2 - Basical Models

• Linear Regression (notebook) (code). Implement a Linear Regression with TensorFlow.
• Logistic Regression (notebook) (code). Implement a Logistic Regression with TensorFlow.
• Multilayer Perceptron Layer (notebook) (code). Implement Multi-Layer Perceptron Model with TensorFlow.
• CNN (notebook) (code). Implement CNN Model with TensorFlow.

3 - Neural Network Architecture

• VGG16 (notebook) (code)(paper). VGG16: Very Deep Convolutional Networks for Large-Scale Image Recognition.
• Resnet (notebook) (code)(paper). Resnet: Deep Residual Learning for Image Recognition.

4 - Object Detection

• RPN (notebook) (code)(paper). RPN: a Region Proposal Network 🔥
• YOLOv3 (notebook) (code)(paper). YOLOv3: An Incremental Improvement.🔥🔥🔥🔥🔥

5 - Image Segmentation

• Unet (notebook) (code)(paper). U-Net: Convolutional Networks for Biomedical Image Segmentation. 🔥🔥
• FCN (notebook) (code)(paper). FCN: Fully Convolutional Networks for Semantic Segmentation. 🔥🔥🔥

6 - Generative Adversarial Networks

• DCGAN (notebook) (code)(paper). Deep Convolutional Generative Adversarial Network.
• Pix2Pix (notebook) (code)(paper). Image-to-Image Translation with Conditional Adversarial Networks.

7 - Reinforcement Learning

• DQN (notebook) (code). deep Q-network (DQN).