"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 ! 🐍🐍🐍🐍🐍🐍
- 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
- 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.
- 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.
- RPN (notebook) (code)(paper). RPN: a Region Proposal Network 🔥
- YOLOv3 (notebook) (code)(paper). YOLOv3: An Incremental Improvement.🔥🔥🔥🔥🔥
- Unet (notebook) (code)(paper). U-Net: Convolutional Networks for Biomedical Image Segmentation. 🔥🔥
- FCN (notebook) (code)(paper). FCN: Fully Convolutional Networks for Semantic Segmentation. 🔥🔥🔥