如果你想深入了解深度学习理论，强烈推荐阅读Deep-Learning-Papers-Reading-Roadmap，该Roadmap整理了深度学习相关的经典论文，在GitHub上，Star 1900+，方便你了解深度学习历史和基础，掌握深度学习方法，明确深度学习应用方向：
1 Deep Learning History and Basics
1.0 Book
1.1 Survey
1.2 Deep Belief Network(DBN)(Milestone of Deep Learning Eve)
1.3 ImageNet Evolution（Deep Learning broke out from here）
1.4 Speech Recognition Evolution
2 Deep Learning Method
2.1 Model
2.2 Optimization
2.3 Unsupervised Learning / Deep Generative Model
2.4 RNN / Sequence-to-Sequence Model
2.5 Neural Turing Machine
2.6 Deep Reinforcement Learning
2.7 Deep Transfer Learning / Lifelong Learning / especially for RL
2.8 One Shot Deep Learning
3 Applications
3.1 NLP(Natural Language Processing)
3.2 Object Detection
3.3 Visual Tracking
3.4 Image Caption
3.5 Machine Translation
3.6 Robotics
3.7 Art
3.8 Object Segmentation
https://github.com/floodsung/Deep-Learning-Papers-Reading-Roadmap
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