Further reading
Here is a list of references that can help you gain more knowledge about the topics that are relevant to this chapter. The following research papers summarize popular use cases of DL:
- CV
- Gradient-based learning applied to document recognition by LeCun et al.
- ImageNet: A Large-Scale Hierarchical Image Database by Deng et al.
- NLP
- A Neural Probabilistic Language Model by Bengio et al.
- Speech Recognition with Deep Recurrent Neural Networks by Grave et al.
- RL
- An Introduction to Deep Reinforcement Learning by François-Lavet et al.
- Generative modeling
- Generative Adversarial Networks by Goodfellow et al.
