<commit_before>## Materials
* [Slides](https://yadi.sk/i/2oUkKL8m3UFFe8)
* Our [lecture](https://yadi.sk/i/-U5w4NpJ3H5TWD) & [seminar](https://yadi.sk/i/W3N7-6is3H5TWN) (russian)
* English lectures
  * Lecture by <NAME> - [cs294 video](https://www.youtube.com/watch?v=fZNyHoXgV7M&index=24&list=PLkFD6_40KJIwTmSbCv9OVJB3YaO4sFwkX)
  * Optional lecture on conversation systems - [video](https://www.youtube.com/watch?v=2tKNpzUvDc4	)
* Will hopefully record our lecture in english soon!
* Self-critical sequence traning [original article](https://arxiv.org/abs/1612.00563)

## Practice
As usual, go to practice_{your framework}.ipynb above and follow instructions from there. [pytorch](https://github.com/yandexdataschool/Practical_RL/blob/master/week8_scst/practice_torch.ipynb), [tensorflow](https://github.com/yandexdataschool/Practical_RL/blob/master/week8_scst/practice_tf.ipynb), [theano](https://github.com/yandexdataschool/Practical_RL/blob/master/week8_scst/practice_theano.ipynb)

Binder quickstart (lasts 1 hour): [![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/yandexdataschool/Practical_RL/master)

## More materials
* An [awesome post](http://distill.pub/2016/augmented-rnns/) explaining attention and long-term memory models.
* [BLEU](http://www.aclweb.org/anthology/P02-1040.pdf) and [CIDEr](https://arxiv.org/pdf/1411.5726.pdf) articles.
* Image captioning
  * MSCOCO captioning [challenge](http://mscoco.org/dataset/#captions-challenge2015)
  * Captioning baseline [notebook](https://github.com/yandexdataschool/HSE_deeplearning/blob/master/week7/captioning_solution_ars.ipynb)
* Other articles on reinforcement learning for natural language: 
  * [task-oriented conversation system](https://arxiv.org/abs/1703.07055)
  * [generating dialogues](https://arxiv.org/abs/1606.01541)
  * [sequential adversarial networks](https://arxiv.org/abs/1609.05473) (a.k.a. SeqGAN)
  * A large overview for machine translation (touching on RL, including RL failures) - [arxiv](https://arxiv.org/abs/1609.08144)
  * How _not_ to evaluate conversation models - [arxiv](https://arxiv.org/abs/1603.08023)
* Overview of other non-games applications ("that article again") - [arxiv](https://arxiv.org/abs/1701.07274)
<commit_msg>new videos<commit_after>## Materials
* [Slides](https://yadi.sk/i/2oUkKL8m3UFFe8)
* Our [lecture](https://yadi.sk/i/hmjUfKht3UNCSq) & [seminar](https://yadi.sk/i/dTkWTFNj3UNCTv) (russian)
* English lectures
  * Lecture by <NAME> - [cs294 video](https://www.youtube.com/watch?v=fZNyHoXgV7M&index=24&list=PLkFD6_40KJIwTmSbCv9OVJB3YaO4sFwkX)
  * Optional lecture on conversation systems - [video](https://www.youtube.com/watch?v=2tKNpzUvDc4	)
* Will hopefully record our lecture in english soon!
* Self-critical sequence traning [original article](https://arxiv.org/abs/1612.00563)

## Practice
As usual, go to practice_{your framework}.ipynb above and follow instructions from there. [pytorch](https://github.com/yandexdataschool/Practical_RL/blob/master/week8_scst/practice_torch.ipynb), [tensorflow](https://github.com/yandexdataschool/Practical_RL/blob/master/week8_scst/practice_tf.ipynb), [theano](https://github.com/yandexdataschool/Practical_RL/blob/master/week8_scst/practice_theano.ipynb)

Binder quickstart (lasts 1 hour): [![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/yandexdataschool/Practical_RL/master)

## More materials
* An [awesome post](http://distill.pub/2016/augmented-rnns/) explaining attention and long-term memory models.
* [BLEU](http://www.aclweb.org/anthology/P02-1040.pdf) and [CIDEr](https://arxiv.org/pdf/1411.5726.pdf) articles.
* Image captioning
  * MSCOCO captioning [challenge](http://mscoco.org/dataset/#captions-challenge2015)
  * Captioning baseline [notebook](https://github.com/yandexdataschool/HSE_deeplearning/blob/master/week7/captioning_solution_ars.ipynb)
* Other articles on reinforcement learning for natural language: 
  * [task-oriented conversation system](https://arxiv.org/abs/1703.07055)
  * [generating dialogues](https://arxiv.org/abs/1606.01541)
  * [sequential adversarial networks](https://arxiv.org/abs/1609.05473) (a.k.a. SeqGAN)
  * A large overview for machine translation (touching on RL, including RL failures) - [arxiv](https://arxiv.org/abs/1609.08144)
  * How _not_ to evaluate conversation models - [arxiv](https://arxiv.org/abs/1603.08023)
* Overview of other non-games applications ("that article again") - [arxiv](https://arxiv.org/abs/1701.07274)

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