참고사이트:
- http://cs224d.stanford.edu/syllabus.html
- http://web.stanford.edu/class/cs224n/syllabus.html
- http://web.stanford.edu/class/cs124/
- http://cs231n.stanford.edu/syllabus.html
- https://web.stanford.edu/~jurafsky/slp3/
- https://github.com/nyu-dl/NLP_DL_Lecture_Note/blob/master/lecture_note.pdf
- https://sites.google.com/view/seq2seq-icml17
- https://khan.github.io/KaTeX/function-support.html
- https://github.com/OpenNMT/OpenNMT-py/
- https://machinelearningmastery.com/applications-of-deep-learning-for-natural-language-processing/ http://ruder.io/deep-learning-nlp-best-practices/
- Oxford NLP lecture notes
앞으로 읽어야 할 것들:
- Text Classificaion
- MT
- Summarization
- RL (Policy Gradient)
- SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient
- BATCH POLICY GRADIENT METHODS FOR IMPROVING NEURAL CONVERSATION MODELS
- AN ACTOR-CRITIC ALGORITHM FOR SEQUENCE PREDICTION
- REINFORCEMENT LEARNING NEURAL TURING MACHINES
- Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback
- On Monte Carlo Tree Search and Reinforcement Learning
- DEEP REINFORCEMENT LEARNING: AN OVERVIEW
- Asynchronous Methods for Deep Reinforcement Learning
- Evolution Strategies as a Scalable Alternative to Reinforcement Learning
- A3C Slides
- Asynchronous Methods for Deep Reinforcement Learning
- Speech Recognition
- Chatbot