https://github.com/MorvanZhou/Tensorflow-Tutorial

Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学
https://github.com/MorvanZhou/Tensorflow-Tutorial

autoencoder classification cnn deep-q-network dqn dropout gan generative-adversarial-network machine-learning neural-network regression rnn tensorflow tensorflow-tutorials tutorial

Last synced: about 1 month ago
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Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学

• Host: GitHub
• URL: https://github.com/MorvanZhou/Tensorflow-Tutorial
• Owner: MorvanZhou
• License: mit
• Created: 2017-05-10T11:02:32.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2020-10-31T02:48:09.000Z (about 4 years ago)
• Last Synced: 2024-11-11T15:12:01.757Z (about 1 month ago)
• Topics: autoencoder, classification, cnn, deep-q-network, dqn, dropout, gan, generative-adversarial-network, machine-learning, neural-network, regression, rnn, tensorflow, tensorflow-tutorials, tutorial
• Language: Python
• Homepage: https://mofanpy.com/tutorials/machine-learning/tensorflow/
• Size: 37.1 MB
• Stars: 4,332
• Watchers: 258
• Forks: 1,882
• Open Issues: 8
• Metadata Files:
  • Readme: README.md

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README

        
### If you'd like to use **PyTorch**, no worries, I made a new **PyTorch Tutorial** just like Tensorflow. Here is the link: [https://github.com/MorvanZhou/PyTorch-Tutorial](https://github.com/MorvanZhou/PyTorch-Tutorial)

# Tensorflow 2017 Tutorials

**Tensorflow 2+ has been released, [here](https://github.com/MorvanZhou/Tensorflow2-Tutorial) is my quick TF2+ tutorial codes**

In these tutorials, we will build our first Neural Network and try to build some advanced Neural Network architectures developed recent years.

All methods mentioned below have their video and text tutorial in Chinese. Visit [莫烦 Python](https://mofanpy.com) for more.

* Tensorflow basic

  * [Session](tutorial-contents/201_session.py)

  * [Placeholder](tutorial-contents/202_placeholder.py)

  * [Variable](tutorial-contents/203_variable.py)

  * [Activation](tutorial-contents/204_activation.py)

* Build your first network

  * [Regression](tutorial-contents/301_simple_regression.py)

  * [Classification](tutorial-contents/302_simple_classification.py)

  * [Save and reload](tutorial-contents/303_save_reload.py)

  * [Optimizers](tutorial-contents/304_optimizer.py)

  * [Tensorboard](tutorial-contents/305_tensorboard.py)

  * [Dataset](tutorial-contents/306_dataset.py)

* Advanced neural network

  * [CNN](tutorial-contents/401_CNN.py)

  * [RNN-Classification](tutorial-contents/402_RNN_classification.py)

  * [RNN-Regression](tutorial-contents/403_RNN_regression.py)

  * [AutoEncoder](tutorial-contents/404_AutoEncoder.py)

  * [DQN Reinforcement Learning](tutorial-contents/405_DQN_reinforcement_learning.py)

  * [GAN (Generative Adversarial Nets)](tutorial-contents/406_GAN.py) / [Conditional GAN](tutorial-contents/406_conditional_GAN.py)

  * [Transfer Learning](tutorial-contents/407_transfer_learning.py)

* Others (WIP)

  * [Dropout](tutorial-contents/501_dropout.py)

  * [Batch Normalization](tutorial-contents/502_batch_normalization.py)

  * [Visualize Gradient Descent](tutorial-contents/503_visualize_gradient_descent.py)

  * [Distributed training](tutorial-contents/504_distributed_training.py)

### [Regression](tutorial-contents/301_simple_regression.py)



    



### [Classification](tutorial-contents/302_simple_classification.py)



    



### [CNN](tutorial-contents/401_CNN.py)



    



### [RNN](tutorial-contents/403_RNN_regression.py)



    



### [Autoencoder](tutorial-contents/404_AutoEncoder.py)



    





    



### [GAN (Generative Adversarial Nets)](tutorial-contents/406_GAN.py)



    



### [Dropout](tutorial-contents/501_dropout.py)



    



### [Batch Normalization](tutorial-contents/502_batch_normalization.py)



    



### [Visualize Gradient Descent](tutorial-contents/503_visualize_gradient_descent.py)



    



# Donation

*If this does help you, please consider donating to support me for better tutorials! Any contribution is greatly appreciated!*