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🎉TensorFlow2.0-Examples🎉!

"Talk is cheap, show me the code." ----- Linus Torvalds

Branch Stars Forks Awesome Awesome

Created by YunYang1994

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

Contents

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. 🔥🔥🔥
  • AutoEncoder (notebook) (code)(paper). AutoEncoder: Reducing the Dimensionality of Data with Neural Networks.

4 - Object Detection

  • MTCNN (notebook) (code)(paper). MTCNN: Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks. (Face detection and Alignment) 🔥🔥

  • YOLOv3 (notebook) (code)(paper). YOLOv3: An Incremental Improvement.🔥🔥🔥🔥

  • SSD (notebook) (code)(paper). SSD: Single Shot MultiBox Detector.🔥🔥🔥🔥 【TO DO】

  • Faster R-CNN (notebook) (code)(paper). Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks.🔥🔥🔥🔥 【TO DO】

5 - Image Segmentation

  • FCN (notebook) (code)(paper). FCN: Fully Convolutional Networks for Semantic Segmentation. 🔥🔥🔥🔥🔥

  • Unet (notebook) (code)(paper). U-Net: Convolutional Networks for Biomedical Image 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 - Utils

  • Multiple GPU Training (notebook)(code). Use multiple GPU to train your model.