{"id":13688648,"url":"https://github.com/wagamamaz/tensorflow-tutorial","last_synced_at":"2025-04-04T19:10:33.698Z","repository":{"id":65778943,"uuid":"66577770","full_name":"wagamamaz/tensorflow-tutorial","owner":"wagamamaz","description":"TensorFlow and Deep Learning Tutorials","archived":false,"fork":false,"pushed_at":"2018-02-26T23:00:27.000Z","size":8,"stargazers_count":734,"open_issues_count":0,"forks_count":210,"subscribers_count":65,"default_branch":"master","last_synced_at":"2025-03-28T18:12:21.937Z","etag":null,"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"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/wagamamaz.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2016-08-25T17:11:00.000Z","updated_at":"2025-02-10T05:46:33.000Z","dependencies_parsed_at":"2023-02-09T14:25:26.339Z","dependency_job_id":null,"html_url":"https://github.com/wagamamaz/tensorflow-tutorial","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/wagamamaz%2Ftensorflow-tutorial","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/wagamamaz%2Ftensorflow-tutorial/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/wagamamaz%2Ftensorflow-tutorial/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/wagamamaz%2Ftensorflow-tutorial/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/wagamamaz","download_url":"https://codeload.github.com/wagamamaz/tensorflow-tutorial/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247234921,"owners_count":20905854,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["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"],"created_at":"2024-08-02T15:01:18.704Z","updated_at":"2025-04-04T19:10:33.675Z","avatar_url":"https://github.com/wagamamaz.png","language":null,"funding_links":[],"categories":["Others"],"sub_categories":[],"readme":"# TensorFlow and Deep Learning Tutorials\n\n\u003cdiv align=\"center\"\u003e\n  \u003cdiv class=\"TensorFlow\"\u003e\n    \u003cimg src=\"https://www.tensorflow.org/images/tf_logo_transp.png\" style=\": left; margin-left: 5px; margin-bottom: 5px;\"\u003e\u003cbr\u003e\u003cbr\u003e\n  \u003c/div\u003e\n\u003c/div\u003e\n\n## Google's Deep Learning Tutorials \n\n - [TensorFlow Official Deep Learning Tutorial](https://www.tensorflow.org/versions/master/tutorials/index.html) [[中文]](http://wiki.jikexueyuan.com/project/tensorflow-zh/).\n - 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)\n - 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)\n - 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)\n - 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)\n - 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)\n - 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)\n - 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)\n \n## Deep Learning Reading List\n\n - [MIT Deep Learning Book](http://www.deeplearningbook.org)\n - [Karpathy Blog](http://karpathy.github.io)\n - [Stanford UFLDL Tutorials](http://deeplearning.stanford.edu/tutorial/)\n - [Colah's Blog - Word Embedding](http://colah.github.io/posts/2014-07-NLP-RNNs-Representations/) [[中文]](http://dataunion.org/9331.html)\n - [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==\u0026mid=2649764821\u0026idx=1\u0026sn=dd325565b40fcbad6e90a9398414dede\u0026scene=2\u0026srcid=0505U2iFJ7tfXgB8yPfNkwrA\u0026from=timeline\u0026isappinstalled=0#wechat_redirect)\n \n\n## Tutorial index\n\n#### 0 - Prerequisite\n- Introduction to Machine Learning ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/0_Prerequisite/ml_introduction.ipynb))\n- Introduction to MNIST Dataset ([notebook](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/0_Prerequisite/mnist_dataset_intro.ipynb))\n\n#### 1 - Introduction\n- 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))\n- 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))\n\n#### 2 - Basic Models\n- 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))\n- 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))\n- 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))\n\n#### 3 - Neural Networks\n- 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))\n- 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))\n- 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))\n- 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))\n- Dynamic Recurrent Neural Network (LSTM) ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/3_NeuralNetworks/dynamic_rnn.py))\n- 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))\n\n#### 4 - Utilities\n- 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))\n- 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))\n- Tensorboard - Advanced visualization ([code](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/4_Utils/tensorboard_advanced.py))\n\n#### 5 - Multi GPU\n- 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))\n\n## Dataset\nSome examples require MNIST dataset for training and testing. Don't worry, this dataset will automatically be downloaded when running examples (with input_data.py).\nMNIST 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).\n\nOfficial Website: [http://yann.lecun.com/exdb/mnist/](http://yann.lecun.com/exdb/mnist/)\n\n\n\n## Selected Repositories\n - [jtoy/awesome-tensorflow](https://github.com/jtoy/awesome-tensorflow)\n - [nlintz/TensorFlow-Tutoirals](https://github.com/nlintz/TensorFlow-Tutorials)\n - [adatao/tensorspark](https://github.com/adatao/tensorspark)\n - [ry/tensorflow-resnet](https://github.com/ry/tensorflow-resnet)\n\n## Tricks\n - [Tricks to use TensorLayer](https://github.com/wagamamaz/tensorlayer-tricks)\n\n## Examples\n\n## Basics\n - Multi-layer perceptron (MNIST) - Classification task, see [tutorial\\_mnist\\_simple.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_mnist_simple.py).\n - 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).\n\n\n## Computer Vision\n - Denoising Autoencoder (MNIST). Classification task, see [tutorial_mnist.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_mnist.py).\n - Stacked Denoising Autoencoder and Fine-Tuning (MNIST). Classification task, see [tutorial_mnist.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_mnist.py).\n - Convolutional Network (MNIST). Classification task, see [tutorial_mnist.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_mnist.py).\n - 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).\n - VGG 16 (ImageNet). Classification task, see [tutorial_vgg16.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_vgg16.py).\n - VGG 19 (ImageNet). Classification task, see [tutorial_vgg19.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_vgg19.py).\n - InceptionV3 (ImageNet). Classification task, see [tutorial\\_inceptionV3_tfslim.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_inceptionV3_tfslim.py).\n - Wide ResNet (CIFAR) by [ritchieng](https://github.com/ritchieng/wideresnet-tensorlayer).\n - More CNN implementations of [TF-Slim](https://github.com/tensorflow/models/tree/master/research/slim) can be connected to TensorLayer via SlimNetsLayer.\n - [Spatial Transformer Networks](https://arxiv.org/abs/1506.02025) by [zsdonghao](https://github.com/zsdonghao/Spatial-Transformer-Nets).\n - [U-Net for brain tumor segmentation](https://github.com/zsdonghao/u-net-brain-tumor) by [zsdonghao](https://github.com/zsdonghao/u-net-brain-tumor).\n - Variational Autoencoder (VAE) for (CelebA) by [yzwxx](https://github.com/yzwxx/vae-celebA).\n - Variational Autoencoder (VAE) for (MNIST) by [BUPTLdy](https://github.com/BUPTLdy/tl-vae).\n - Image Captioning - Reimplementation of Google's [im2txt](https://github.com/tensorflow/models/tree/master/research/im2txt) by [zsdonghao](https://github.com/zsdonghao/Image-Captioning).\n\n## Natural Language Processing\n - 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).\n - 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).\n - 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).\n - 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).\n - Chinese Text Anti-Spam by [pakrchen](https://github.com/pakrchen/text-antispam).\n - [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).\n - 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).\n\n## Adversarial Learning\n- DCGAN (CelebA). Generating images by [Deep Convolutional Generative Adversarial Networks](http://arxiv.org/abs/1511.06434) by [zsdonghao](https://github.com/zsdonghao/dcgan).\n- [Generative Adversarial Text to Image Synthesis](https://github.com/zsdonghao/text-to-image) by [zsdonghao](https://github.com/zsdonghao/text-to-image).\n- [Unsupervised Image to Image Translation with Generative Adversarial Networks](https://github.com/zsdonghao/Unsup-Im2Im) by [zsdonghao](https://github.com/zsdonghao/Unsup-Im2Im).\n- [Improved CycleGAN](https://github.com/luoxier/CycleGAN_Tensorlayer) with resize-convolution by [luoxier](https://github.com/luoxier/CycleGAN_Tensorlayer)\n- [Super Resolution GAN](https://arxiv.org/abs/1609.04802) by [zsdonghao](https://github.com/zsdonghao/SRGAN).\n- [DAGAN: Fast Compressed Sensing MRI Reconstruction](https://github.com/nebulaV/DAGAN) by [nebulaV](https://github.com/nebulaV/DAGAN).\n\n## Reinforcement Learning\n - Policy Gradient / Network (Atari Ping Pong), see [tutorial\\_atari_pong.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_atari_pong.py).\n - Deep Q-Network (Frozen lake), see [tutorial\\_frozenlake_dqn.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_frozenlake_dqn.py).\n - 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).\n - Asynchronous Policy Gradient using TensorDB (Atari Ping Pong) by [nebulaV](https://github.com/akaraspt/tl_paper).\n - AC for discrete action space (Cartpole), see [tutorial\\_cartpole_ac.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_cartpole_ac.py).\n - 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).\n - [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).\n - [TRPO](https://arxiv.org/abs/1502.05477) for continuous and discrete action space by [jjkke88](https://github.com/jjkke88/RL_toolbox).\n\n## Miscellaneous\n - 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).\n - Merge TF-Slim into TensorLayer. [tutorial\\_inceptionV3_tfslim.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_inceptionV3_tfslim.py).\n - Merge Keras into TensorLayer. [tutorial_keras.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_keras.py).\n - 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).\n - Data augmentation with TensorLayer, see [tutorial\\_image_preprocess.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_image_preprocess.py).\n - TensorDB by [fangde](https://github.com/fangde) see [here](https://github.com/akaraspt/tl_paper).\n- A simple web service - [TensorFlask](https://github.com/JoelKronander/TensorFlask) by [JoelKronander](https://github.com/JoelKronander).\n- Float 16 half-precision model, see [tutorial\\_mnist_float16.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_mnist_float16.py)\n\n \n### Useful Links\n - [Tricks to use TensorLayer](https://github.com/wagamamaz/tensorlayer-tricks)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwagamamaz%2Ftensorflow-tutorial","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fwagamamaz%2Ftensorflow-tutorial","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwagamamaz%2Ftensorflow-tutorial/lists"}