Tensorflow2.0 Examples

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This tutorial was designed for easily diving into TensorFlow2.0. it includes both notebooks and source codes with explanation.

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 - Image Classification

• ResNet (notebook) (code). Deep Residual Learning for Image Recognition.

4 - Object Detection

• YOLOV3 (notebook) (code). YOLOv3: An Incremental Improvement.

5 - Generative Adversarial Networks

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

6 - Reinforcement Learning

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

7 - Utilities