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TensorFlow and Deep Learning Tutorials
https://github.com/wagamamaz/tensorflow-tutorial
autoencoder cnn convolutional-neural-networks deep-learning deep-learning-tutorial deep-reinforcement-learning keras machine-learning multi-layer-perceptron neural-machine-translation neural-network neural-networks nlp notebook recurrent-neural-networks reinforcement-learning tensorflow tensorflow-tutorials tensorlayer tflearn
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TensorFlow and Deep Learning Tutorials
Host: GitHub
URL: https://github.com/wagamamaz/tensorflow-tutorial
Owner: wagamamaz
Created: 2016-08-25T17:11:00.000Z (over 8 years ago)
Default Branch: master
Last Pushed: 2018-02-26T23:00:27.000Z (almost 7 years ago)
Last Synced: 2025-02-08T11:09:49.832Z (13 days ago)
Topics: autoencoder, cnn, convolutional-neural-networks, deep-learning, deep-learning-tutorial, deep-reinforcement-learning, keras, machine-learning, multi-layer-perceptron, neural-machine-translation, neural-network, neural-networks, nlp, notebook, recurrent-neural-networks, reinforcement-learning, tensorflow, tensorflow-tutorials, tensorlayer, tflearn
Homepage:
Size: 7.81 KB
Stars: 733
Watchers: 66
Forks: 210
Open Issues: 0
Metadata Files:
- Readme: README.md
Awesome Lists containing this project

README

        # TensorFlow and Deep Learning Tutorials



  

    



  



## Google's Deep Learning Tutorials 

 - [TensorFlow Official Deep Learning Tutorial](https://www.tensorflow.org/versions/master/tutorials/index.html) [[中文]](http://wiki.jikexueyuan.com/project/tensorflow-zh/).

 - MLP with Dropout [TensorFlow](https://www.tensorflow.org/versions/master/tutorials/mnist/beginners/index.html) [[中文]](http://wiki.jikexueyuan.com/project/tensorflow-zh/tutorials/mnist_beginners.html)  [TensorLayer](http://tensorlayer.readthedocs.io/en/latest/user/tutorial.html#tensorlayer-is-simple) [[中文]](http://tensorlayercn.readthedocs.io/zh/latest/user/tutorial.html#tensorlayer)

 - Autoencoder [TensorLayer](http://tensorlayercn.readthedocs.io/zh/latest/user/tutorial.html#tensorlayer) [[中文]](http://tensorlayercn.readthedocs.io/zh/latest/user/tutorial.html#denoising-autoencoder)

 - Convolutional Neural Network [TensorFlow](https://www.tensorflow.org/versions/master/tutorials/mnist/pros/index.html) [[中文]](http://wiki.jikexueyuan.com/project/tensorflow-zh/tutorials/mnist_pros.html)  [TensorLayer](http://tensorlayer.readthedocs.io/en/latest/user/tutorial.html#convolutional-neural-network-cnn) [[中文]](http://tensorlayercn.readthedocs.io/zh/latest/user/tutorial.html#convolutional-neural-network)

 - Recurrent Neural Network [TensorFlow](https://www.tensorflow.org/versions/master/tutorials/recurrent/index.html#recurrent-neural-networks) [[中文]](http://wiki.jikexueyuan.com/project/tensorflow-zh/tutorials/recurrent.html)  [TensorLayer](http://tensorlayer.readthedocs.io/en/latest/user/tutorial.html#understand-lstm) [[中文]](http://tensorlayercn.readthedocs.io/zh/latest/user/tutorial.html#lstm)

 - Deep Reinforcement Learning [TensorLayer](http://tensorlayer.readthedocs.io/en/latest/user/tutorial.html#understand-reinforcement-learning) [[中文]](http://tensorlayercn.readthedocs.io/zh/latest/user/tutorial.html#id13)

 - Sequence to Sequence [TensorFlow](https://www.tensorflow.org/versions/master/tutorials/seq2seq/index.html#sequence-to-sequence-models)  [TensorLayer](http://tensorlayer.readthedocs.io/en/latest/user/tutorial.html#understand-translation)[[中文]](http://tensorlayercn.readthedocs.io/zh/latest/user/tutorial.html#id30)

 - Word Embedding [TensorFlow](https://www.tensorflow.org/versions/master/tutorials/word2vec/index.html#vector-representations-of-words) [[中文]](http://wiki.jikexueyuan.com/project/tensorflow-zh/tutorials/word2vec.html)  [TensorLayer](http://tensorlayer.readthedocs.io/en/latest/user/tutorial.html#understand-word-embedding) [[中文]](http://tensorlayercn.readthedocs.io/zh/latest/user/tutorial.html#word-embedding)

 

## Deep Learning Reading List

 - [MIT Deep Learning Book](http://www.deeplearningbook.org)

 - [Karpathy Blog](http://karpathy.github.io)

 - [Stanford UFLDL Tutorials](http://deeplearning.stanford.edu/tutorial/)

 - [Colah's Blog - Word Embedding](http://colah.github.io/posts/2014-07-NLP-RNNs-Representations/) [[中文]](http://dataunion.org/9331.html)

 - [Colah's Blog - Understand LSTN](http://colah.github.io/posts/2015-08-Understanding-LSTMs/) [[门函数]](http://mp.weixin.qq.com/s?__biz=MzI3NDExNDY3Nw==&mid=2649764821&idx=1&sn=dd325565b40fcbad6e90a9398414dede&scene=2&srcid=0505U2iFJ7tfXgB8yPfNkwrA&from=timeline&isappinstalled=0#wechat_redirect)

 

## Tutorial index

#### 0 - Prerequisite

- Introduction to Machine Learning ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/0_Prerequisite/ml_introduction.ipynb))

- Introduction to MNIST Dataset ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/0_Prerequisite/mnist_dataset_intro.ipynb))

#### 1 - Introduction

- Hello World ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/1_Introduction/helloworld.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/1_Introduction/helloworld.py))

- Basic Operations ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/1_Introduction/basic_operations.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/1_Introduction/basic_operations.py))

#### 2 - Basic Models

- Nearest Neighbor ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/2_BasicModels/nearest_neighbor.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/2_BasicModels/nearest_neighbor.py))

- Linear Regression ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/2_BasicModels/linear_regression.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/2_BasicModels/linear_regression.py))

- Logistic Regression ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/2_BasicModels/logistic_regression.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/2_BasicModels/logistic_regression.py))

#### 3 - Neural Networks

- Multilayer Perceptron ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/3_NeuralNetworks/multilayer_perceptron.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/3_NeuralNetworks/multilayer_perceptron.py))

- Convolutional Neural Network ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/3_NeuralNetworks/convolutional_network.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/3_NeuralNetworks/convolutional_network.py))

- Recurrent Neural Network (LSTM) ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/3_NeuralNetworks/recurrent_network.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/3_NeuralNetworks/recurrent_network.py))

- Bidirectional Recurrent Neural Network (LSTM) ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/3_NeuralNetworks/bidirectional_rnn.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/3_NeuralNetworks/bidirectional_rnn.py))

- Dynamic Recurrent Neural Network (LSTM) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/3_NeuralNetworks/dynamic_rnn.py))

- AutoEncoder ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/3_NeuralNetworks/autoencoder.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/3_NeuralNetworks/autoencoder.py))

#### 4 - Utilities

- Save and Restore a model ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/4_Utils/save_restore_model.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/4_Utils/save_restore_model.py))

- Tensorboard - Graph and loss visualization ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/4_Utils/tensorboard_basic.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/4_Utils/tensorboard_basic.py))

- Tensorboard - Advanced visualization ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/4_Utils/tensorboard_advanced.py))

#### 5 - Multi GPU

- Basic Operations on multi-GPU ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/5_MultiGPU/multigpu_basics.ipynb)) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/5_MultiGPU/multigpu_basics.py))

## Dataset

Some examples require MNIST dataset for training and testing. Don't worry, this dataset will automatically be downloaded when running examples (with input_data.py).

MNIST is a database of handwritten digits, for a quick description of that dataset, you can check [this notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/0_Prerequisite/mnist_dataset_intro.ipynb).

Official Website: [http://yann.lecun.com/exdb/mnist/](http://yann.lecun.com/exdb/mnist/)

## Selected Repositories

 - [jtoy/awesome-tensorflow](https://github.com/jtoy/awesome-tensorflow)

 - [nlintz/TensorFlow-Tutoirals](https://github.com/nlintz/TensorFlow-Tutorials)

 - [adatao/tensorspark](https://github.com/adatao/tensorspark)

 - [ry/tensorflow-resnet](https://github.com/ry/tensorflow-resnet)

## Tricks

 - [Tricks to use TensorLayer](https://github.com/wagamamaz/tensorlayer-tricks)

## Examples

## Basics

 - Multi-layer perceptron (MNIST) - Classification task, see [tutorial\_mnist\_simple.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_mnist_simple.py).

 - Multi-layer perceptron (MNIST) - Classification using Iterator, see [method1](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_mlp_dropout1.py) and [method2](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_mlp_dropout2.py).

## Computer Vision

 - Denoising Autoencoder (MNIST). Classification task, see [tutorial_mnist.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_mnist.py).

 - Stacked Denoising Autoencoder and Fine-Tuning (MNIST). Classification task, see [tutorial_mnist.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_mnist.py).

 - Convolutional Network (MNIST). Classification task, see [tutorial_mnist.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_mnist.py).

 - Convolutional Network (CIFAR-10). Classification task, see [tutorial\_cifar10.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_cifar10.py) and [tutorial\_cifar10_tfrecord.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_cifar10_tfrecord.py).

 - VGG 16 (ImageNet). Classification task, see [tutorial_vgg16.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_vgg16.py).

 - VGG 19 (ImageNet). Classification task, see [tutorial_vgg19.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_vgg19.py).

 - InceptionV3 (ImageNet). Classification task, see [tutorial\_inceptionV3_tfslim.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_inceptionV3_tfslim.py).

 - Wide ResNet (CIFAR) by [ritchieng](https://github.com/ritchieng/wideresnet-tensorlayer).

 - More CNN implementations of [TF-Slim](https://github.com/tensorflow/models/tree/master/research/slim) can be connected to TensorLayer via SlimNetsLayer.

 - [Spatial Transformer Networks](https://arxiv.org/abs/1506.02025) by [zsdonghao](https://github.com/zsdonghao/Spatial-Transformer-Nets).

 - [U-Net for brain tumor segmentation](https://github.com/zsdonghao/u-net-brain-tumor) by [zsdonghao](https://github.com/zsdonghao/u-net-brain-tumor).

 - Variational Autoencoder (VAE) for (CelebA) by [yzwxx](https://github.com/yzwxx/vae-celebA).

 - Variational Autoencoder (VAE) for (MNIST) by [BUPTLdy](https://github.com/BUPTLdy/tl-vae).

 - Image Captioning - Reimplementation of Google's [im2txt](https://github.com/tensorflow/models/tree/master/research/im2txt) by [zsdonghao](https://github.com/zsdonghao/Image-Captioning).

## Natural Language Processing

 - Recurrent Neural Network (LSTM). Apply multiple LSTM to PTB dataset for language modeling, see [tutorial_ptb_lstm.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_ptb_lstm.py) and [tutorial\_ptb\_lstm\_state\_is_tuple.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_ptb_lstm_state_is_tuple.py).

 - Word Embedding (Word2vec). Train a word embedding matrix, see [tutorial\_word2vec_basic.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial\_word2vec_basic.py).

 - Restore Embedding matrix. Restore a pre-train embedding matrix, see [tutorial\_generate_text.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_generate_text.py).

 - Text Generation. Generates new text scripts, using LSTM network, see [tutorial\_generate_text.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_generate_text.py).

 - Chinese Text Anti-Spam by [pakrchen](https://github.com/pakrchen/text-antispam).

 - [Chatbot in 200 lines of code](https://github.com/zsdonghao/seq2seq-chatbot) for [Seq2Seq](http://tensorlayer.readthedocs.io/en/latest/modules/layers.html#simple-seq2seq).

 - FastText Sentence Classification (IMDB), see [tutorial\_imdb\_fasttext.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_imdb_fasttext.py) by [tomtung](https://github.com/tomtung).

## Adversarial Learning

- DCGAN (CelebA). Generating images by [Deep Convolutional Generative Adversarial Networks](http://arxiv.org/abs/1511.06434) by [zsdonghao](https://github.com/zsdonghao/dcgan).

- [Generative Adversarial Text to Image Synthesis](https://github.com/zsdonghao/text-to-image) by [zsdonghao](https://github.com/zsdonghao/text-to-image).

- [Unsupervised Image to Image Translation with Generative Adversarial Networks](https://github.com/zsdonghao/Unsup-Im2Im) by [zsdonghao](https://github.com/zsdonghao/Unsup-Im2Im).

- [Improved CycleGAN](https://github.com/luoxier/CycleGAN_Tensorlayer) with resize-convolution by [luoxier](https://github.com/luoxier/CycleGAN_Tensorlayer)

- [Super Resolution GAN](https://arxiv.org/abs/1609.04802) by [zsdonghao](https://github.com/zsdonghao/SRGAN).

- [DAGAN: Fast Compressed Sensing MRI Reconstruction](https://github.com/nebulaV/DAGAN) by [nebulaV](https://github.com/nebulaV/DAGAN).

## Reinforcement Learning

 - Policy Gradient / Network (Atari Ping Pong), see [tutorial\_atari_pong.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_atari_pong.py).

 - Deep Q-Network (Frozen lake), see [tutorial\_frozenlake_dqn.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_frozenlake_dqn.py).

 - Q-Table learning algorithm (Frozen lake), see [tutorial\_frozenlake\_q_table.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_frozenlake_q_table.py).

 - Asynchronous Policy Gradient using TensorDB (Atari Ping Pong) by [nebulaV](https://github.com/akaraspt/tl_paper).

 - AC for discrete action space (Cartpole), see [tutorial\_cartpole_ac.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_cartpole_ac.py).

 - A3C for continuous action space (Bipedal Walker), see [tutorial\_bipedalwalker_a3c*.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_bipedalwalker_a3c_continuous_action.py).

 - [DAGGER](https://www.cs.cmu.edu/%7Esross1/publications/Ross-AIStats11-NoRegret.pdf) for ([Gym Torcs](https://github.com/ugo-nama-kun/gym_torcs)) by [zsdonghao](https://github.com/zsdonghao/Imitation-Learning-Dagger-Torcs).

 - [TRPO](https://arxiv.org/abs/1502.05477) for continuous and discrete action space by [jjkke88](https://github.com/jjkke88/RL_toolbox).

## Miscellaneous

 - Distributed Training. [mnist](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_mnist_distributed.py) and [imagenet](https://github.com/tensorlayer/tensorlayer/blob/master/example/tutorial_imagenet_inceptionV3_distributed.py) by [jorgemf](https://github.com/jorgemf).

 - Merge TF-Slim into TensorLayer. [tutorial\_inceptionV3_tfslim.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_inceptionV3_tfslim.py).

 - Merge Keras into TensorLayer. [tutorial_keras.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_keras.py).

 - Data augmentation with TFRecord. Effective way to load and pre-process data, see [tutorial_tfrecord*.py](https://github.com/zsdonghao/tensorlayer/tree/master/example) and [tutorial\_cifar10_tfrecord.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_cifar10_tfrecord.py).

 - Data augmentation with TensorLayer, see [tutorial\_image_preprocess.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_image_preprocess.py).

 - TensorDB by [fangde](https://github.com/fangde) see [here](https://github.com/akaraspt/tl_paper).

- A simple web service - [TensorFlask](https://github.com/JoelKronander/TensorFlask) by [JoelKronander](https://github.com/JoelKronander).

- Float 16 half-precision model, see [tutorial\_mnist_float16.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_mnist_float16.py)

 

### Useful Links

 - [Tricks to use TensorLayer](https://github.com/wagamamaz/tensorlayer-tricks)