1.如何开启深度学习之旅？这三大类125篇论文为你导航（附资源下载）

https://www.jiqizhixin.com/articles/375cf437-4690-4308-b538-afe9d8cb2b89

2.卷积神经网络的推导和实现

http://cogprints.org/5869/1/cnn_tutorial.pdf

3.LeNet论文

http://vision.stanford.edu/cs598_spring07/papers/Lecun98.pdf

4.AlexNet论文

http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf

5.VGGNet论文

http://www.robots.ox.ac.uk/~vgg/research/very_deep/

6.NIN(Network in Network)论文

https://arxiv.org/abs/1312.4400

7.GoogLeNet论文

https://arxiv.org/abs/1409.4842

8.ResNet(Residual Network，残差网络)

https://arxiv.org/abs/1512.03385

9.RL(reinforcement learning，强化学习)

10.深度森林

https://arxiv.org/abs/1702.08835

11.艺术风格的神经网络算法（A Nerual Algorithm of Artistic Style)

https://arxiv.org/pdf/1508.06576v2.pdf

12.作曲风格的深度学习创作，代码实现

https://github.com/tensorflow/magenta