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The deeplearning algorithms are carefully implemented by [tensorflow](https://www.tensorflow.org/).
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### Environment
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- Python 3.5
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- tensorflow 0.12
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- tensorflow 1.4
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- pytorch 0.2.0
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### The deeplearning algorithms includes (now):
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- Logistic Regression [logisticRegression.py](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/models/logisticRegression.py)
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- 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)]
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- SqueezeNet [[self](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/CNNs/SqueezeNet.py) [paper](https://arxiv.org/abs/1602.07360)]
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- 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)]
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- ShuffleNet [[self](https://github.com/xiaohu2015/DeepLearning_tutorials/blob/master/CNNs/ShuffleNet.py) by pytorch [paper](http://cn.arxiv.org/pdf/1707.01083v2)]
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