{"id":15026013,"url":"https://github.com/xiaohu2015/deeplearning_tutorials","last_synced_at":"2025-04-08T08:12:30.850Z","repository":{"id":38237672,"uuid":"76567679","full_name":"xiaohu2015/DeepLearning_tutorials","owner":"xiaohu2015","description":"The deeplearning algorithms implemented by tensorflow","archived":false,"fork":false,"pushed_at":"2019-02-27T02:31:07.000Z","size":12025,"stargazers_count":1833,"open_issues_count":9,"forks_count":772,"subscribers_count":76,"default_branch":"master","last_synced_at":"2025-04-08T08:12:20.244Z","etag":null,"topics":["cnn","dbn","deep-learning-algorithms","deep-learning-tutorial","lstm","mlp","rbm","sda","tensorflow"],"latest_commit_sha":null,"homepage":"","language":"Jupyter 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Notebook","readme":"# Deep Learning Tutorials with Tensorflow\nThe deeplearning algorithms are carefully implemented by [tensorflow](https://www.tensorflow.org/).  \n### Environment\n- Python 3.5\n- tensorflow 1.4\n- pytorch 0.2.0\n\n### The deeplearning algorithms includes (now):\n- Logistic Regression  [logisticRegression.py](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/models/logisticRegression.py)\n- Multi-Layer Perceptron (MLP) [mlp.py](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/models/mlp.py)\n- Convolution Neural Network (CNN) [cnn.py](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/models/cnn.py)\n- Denoising Aotoencoder (DA) [da.py](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/models/da.py)\n- Stacked Denoising Autoencoder (SDA) [sda.py](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/models/sda.py)\n- Restricted Boltzmann Machine (RBM) [[rbm.py](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/models/rbm.py)    [gbrbm.py](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/models/gbrbm.py)]\n- Deep Belief Network (DBN) [dbn.py](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/models/dbn.py)\n\nNote: the project aims at imitating the well-implemented algorithms in [Deep Learning Tutorials](http://www.deeplearning.net/tutorial/) (coded by [Theano](http://deeplearning.net/software/theano/index.html)).\n\n### CNN Models\n- MobileNet [[self](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/CNNs/MobileNet.py) [paper](https://arxiv.org/abs/1704.04861) [ref](https://github.com/Zehaos/MobileNet/blob/master/nets/mobilenet.py)]\n- MobileNetv2 [[self](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/CNNs/mobilenet_v2.py) [paper](https://arxiv.org/pdf/1801.04381.pdf) [ref](https://github.com/tensorflow/models/tree/master/research/slim/nets/mobilenet)]\n- SqueezeNet [[self](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/CNNs/SqueezeNet.py) [paper](https://arxiv.org/abs/1602.07360)]\n- ResNet [[self](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/CNNs/ResNet50.py) [caffe ref](https://github.com/KaimingHe/deep-residual-networks) [paper1](https://arxiv.org/abs/1512.03385) [paper2](https://arxiv.org/abs/1603.05027)]\n- ShuffleNet [[self](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/CNNs/ShuffleNet.py) by pytorch [paper](http://cn.arxiv.org/pdf/1707.01083v2)]\n- ShuffleNetv2 [[self](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/CNNs/shufflenet_v2.py) [ref](https://github.com/tensorpack/tensorpack/blob/master/examples/ImageNetModels/shufflenet.py) [paper](https://arxiv.org/abs/1807.11164)] \n- DenseNet [[self](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/CNNs/densenet.py) [pytorch_ref](https://github.com/pytorch/vision/blob/master/torchvision/models/densenet.py) [paper](https://arxiv.org/abs/1608.06993)]\n\n### Object detection\n- YOLOv1 [[self](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/ObjectDetections/yolo/yolo_tf.py) [paper](https://arxiv.org/abs/1506.02640) [ref](https://github.com/gliese581gg/YOLO_tensorflow)]\n- SSD [[self](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/ObjectDetections/SSD/SSD_demo.py) [paper](https://arxiv.org/pdf/1611.10012.pdf) [slides](http://www.cs.unc.edu/~wliu/papers/ssd_eccv2016_slide.pdf) [cafe](https://github.com/weiliu89/caffe/tree/ssd) [TF](https://arxiv.org/abs/1512.02325) [pytorch](https://github.com/amdegroot/ssd.pytorch) ]\n- YOLOv2 [[self](https://github.com/xiaohu2015/DeepLearning_tutorials/tree/master/ObjectDetections/yolo2) [paper](https://arxiv.org/abs/1612.08242) [ref](https://github.com/yhcc/yolo2)]\n\n### Practical examples\nYou can find more practical examples with tensorflow here:\n- CNN for setence classification [[self](https://github.com/xiaohu2015/DeepLearning_tutorials/tree/master/examples/cnn_setence_classification)] [[blog](http://www.wildml.com/2015/12/implementing-a-cnn-for-text-classification-in-tensorflow/)] [[paper](https://arxiv.org/pdf/1408.5882v2.pdf)]\n- RNN for language model [[self](https://github.com/xiaohu2015/DeepLearning_tutorials/tree/master/examples/rnn_language_model)] [[blog](http://www.wildml.com/2015/09/recurrent-neural-networks-tutorial-part-2-implementing-a-language-model-rnn-with-python-numpy-and-theano/)] [[blog_cn](http://blog.csdn.net/xiaohu2022/article/details/54578013)]\n- LSTM for language model (PTB data) [[self](https://github.com/xiaohu2015/DeepLearning_tutorials/tree/master/examples/lstm_model_ptb)] [[tutorial](https://www.tensorflow.org/versions/r0.12/tutorials/recurrent/index.html#recurrent-neural-networks)] [[paper](https://arxiv.org/pdf/1409.2329.pdf)]\n- VGG model for image classification (object recongnition) [[self](https://github.com/xiaohu2015/DeepLearning_tutorials/tree/master/examples/VGG)] [[source](https://github.com/machrisaa/tensorflow-vgg)]\n- Residual network for cifar10_dataset [[self](https://github.com/xiaohu2015/DeepLearning_tutorials/tree/master/examples/Resnet)] [[source](https://github.com/wenxinxu/resnet-in-tensorflow)] [[paper](https://arxiv.org/pdf/1603.05027v3.pdf)]\n- LSTM for time series prediction [[self](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/examples/lstm_time_series_regression)] [[source](https://github.com/MorvanZhou/tutorials/blob/master/tensorflowTUT/tf20_RNN2.2/full_code.py)]\n- Generative adversarial network (GAN) [[self](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/examples/gan)]\n- Variational autoencoder (VAE) [[self](https://github.com/xiaohu2015/DeepLearning_tutorials/tree/master/examples/VAE)]\n\n### Results\n![1](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/results/filters_corruption_30.png)\n![2](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/results/new_filters_at_epoch_14.png)\n![3](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/results/new_original_and_10samples.png)\n![4](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/results/DBN_results.png)\n![5](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/examples/lstm_time_series_regression/lstm_regression_results.png)\n\n### Fun Blogs\n- [Chatbots with Seq2Seq](http://suriyadeepan.github.io/2016-06-28-easy-seq2seq/)\n\n### Personal Notes\n- Tensorflow for RNNs [[tf_rnn.ipynb](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/notes/tf_rnn.ipynb)]\n- Tensorflow for Autoencoder [[tf_autoencoder.ipynb](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/notes/tf_autoencoder.ipynb)]\n\n### Other Tutorials\n- [ageron/handson-ml\n](https://github.com/ageron/handson-ml/)\n- [Hvass-Labs/TensorFlow-Tutorials\n](https://github.com/Hvass-Labs/TensorFlow-Tutorials)\n- [BinRoot/TensorFlow-Book\n](https://github.com/BinRoot/TensorFlow-Book)\n- [sjchoi86/dl_tutorials_10weeks\n](https://github.com/sjchoi86/dl_tutorials_10weeks)\n\n#### Don't hesitate to star this project if it is helpful!\n### If you benefit from the tutorial, please make a small donation by WeChat sweep.\n![weichat](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/results/weichat.jpg)\n## 微信号：xiaoxiaohu1994\n## 欢迎关注微信公众号：机器学习算法全栈工程师(Jeemy110)\n![公众号](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/results/654362565405877642.jpg)\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fxiaohu2015%2Fdeeplearning_tutorials","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fxiaohu2015%2Fdeeplearning_tutorials","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fxiaohu2015%2Fdeeplearning_tutorials/lists"}