This description includes all sources and links for our Kaggle competition and materials related to DL learning, Pytorch and Tensorflow. You can add good references about Deep Learning, and put the links under corresponding section. Remember, don't push articles or datasets directly to the github. For articles, please put the links in README.md file under "Papers" section For datesets, build a script that can download datasets automatically, or use remote datasets on AWS S3.

1. Deep Learning RoadMap
   DL Learning path
2. Reinforcement Learning guide
3. CS231n slides and notes
4. Deep learning book
5. UFLDL
6. DL Tutorial
7. DL Tutorial
8. Awesome-deep-vision
9. NLP resources
10. notes
11. Transfer learning
12. fast ai DL course
13. Deep learning course with notes and lab

1. torch_rl : A starting Reinforcement Learning PyTorch Library
2. PyTorch可用的VGG模型
3. pynotebook about pytorch
4. Pytorch Container
5. pytorch net
6. pytorch squeezenet
7. pytorch FlowNets
8. Kaggle cat vs Dog 这是很不错的一个参考材料！
9. pytorch practice
10. Seq2seq pytorch
11. pytorch notebooks
12. pytorch pre-train model zoo(tensorflow)
13. simple pytorch example
14. pytorch practice
15. pytorch tutorial
16. pytorch resource
17. neural talk by pytorch
    neural talk paper1
    neural talk paper2
18. pytorch implement caffe resnet
19. pytorch openNMT github
20. pytorch exercise

1. Intro to Tensorflow
2. Faster-rcnn
   论文链接
3. keras toolbox
4. Tensorflow for ML
5. tensorflow GAN
6. ssd
   ssd github
7. RCNN ssd github 还有很多repo,可以google
8. Machine learning with tensorflow book
9. tensorflow notebook
10. tensorflow exercise
11. DL experiments tensorflow
12. DL resource
13. Tensorflow code review
14. Multi class text classification with CNN,RNN

1. Wasserstein GAN 这篇文章可以重点读一下！
   pytorch code
   Keras code
   讲解Wasserstein GAN的blog
   Generative-models
   Generate images by Generative model Towards Principled Methods for Training Generative Adversarial Networks
2. AI core work
3. Deep Pose 这篇文章以后可能会用到
4. Adversarial Learning for Neural Dialogue Generation 这篇文章很吊，目标是图灵测试
5. CVPR-2016
6. ICCV 2015(ICCV两年一次，16年未开)
7. CVPR 2015
8. ICPR 2014
9. PAMI(需要登陆或充值，IEEE的库用学校网络或许可以直接查看)
10. ICLR 2017
11. A Deep Convolutional Auto-Encoder with Pooling - Unpooling Layers in Caffe
12. NLP 进展
13. Attributing a deep network’s prediction to its input features
14. mask RCNN

1. Machine Learning Video resource
2. MIT Intro to deep learning
3. cs294:Tensorflow for Deep Learning Research
4. DL school
5. Hugo's DL course
6. Videos list on DL

1. Kaggle past solutions
2. Deep Learning by examples
3. GAN for Galaxy

1. Youtube 视频标记数据集

1. RL github project
2. RL Intro book

1. 面试题

1. 推荐系统，DeepFM
2. Python factor analysis library
3. https://arxiv.org/pdf/1703.06843.pdf