hellocybernetics / Tensorflow2.0_eager_execution_tutorials
Tutorials of TensorFlow eager execution
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TensorFlow2.0_Eager_Execution_Tutorials
This repository provides tutorial code of TensorFlow2.0 . This tutorials refer to the PyTorch tutorials
https://github.com/yunjey/pytorch-tutorial
Table of Contents
0. Low Level
1. Basics
2. Intermediate
- Convolutional Neural Network
- Convolutional Neural Network using Keras API
- Deep Residual Network
- Deep Residual Network using Keras API
- Recurrent Neural Network using Keras API
- Bidirectional Recurrent Neural Network using Keras API
- Language Model (RNN-LM)
3. Advanced
- Generative Adversarial Network
- Variational Auto-Encoder
- Graph Convolution
- Neural Style Transfer
- Image Captioning (CNN-RNN)
4. Probability
- MCMC Regression with JointDistribution
- Variational Regression with JointDistribution
- basic modeling with tfp.layers
X. Others
- Hyper Parameter Optmization
- eager vs pytorch speed
- learning discontinuity
- dropout bayes neural network
Dependencies
My environment is Google Colab or
Python 3.7
TensorFlow 2.0 TensorFlow Probability 0.9.0 (nightly)
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