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.
3 - Neural Network Architecture
- VGG16 (notebook) (code)(paper). VGG16: Very Deep Convolutional Networks for Large-Scale Image Recognition
4 - Object Detection
- YOLOv3 (notebook) (code)(paper). YOLOv3: An Incremental Improvement.
π₯ π₯ π₯ π₯ π₯ - RPN (notebook) (code). RegionProposal Network, Backbone of Faster R-CNN
π₯ π₯ π₯
5 - 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.