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韩国大学 yunjey
该存储库提供深入学习研究人员学习PyTorch的教程代码。在本教程中,大多数模型都使用少于30行代码实现。在开始本教程之前,建议您完成官方Pytorch教程(http://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html)。
PyTorch基础知识
https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/01-basics/pytorch_basics/main.py
线性回归
https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/01-basics/linear_regression/main.py#L24-L31
逻辑回归
https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/01-basics/logistic_regression/main.py#L35-L42
前馈神经网络
https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/01-basics/feedforward_neural_network/main.py#L36-L47
二、中级
卷积神经网络
https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/02-intermediate/convolutional_neural_network/main.py#L33-L53
深层残留网络
https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/02-intermediate/deep_residual_network/main.py#L67-L103
经常性神经网络
https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/02-intermediate/recurrent_neural_network/main.py#L38-L56
双向循环神经网络
https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/02-intermediate/bidirectional_recurrent_neural_network/main.py#L38-L57
语言模型(RNN-LM)
https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/02-intermediate/language_model/main.py#L28-L53
生成对抗网络
https://github.com/yunjey/pytorch-tutorial/blob/master/tutorials/02-intermediate/generative_adversarial_network/main.py#L34-L50
三、高级
图像字幕(CNN-RNN)
https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/03-advanced/image_captioning
深卷积GAN(DCGAN)
https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/03-advanced/deep_convolutional_gan
变分自动编码器
https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/03-advanced/variational_auto_encoder
神经风格转移
https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/03-advanced/neural_style_transfer
四、实用工具
TensorBoard在PyTorch
https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/04-utils/tensorboard
系统学习,进入全球人工智能学院