REFERENCES.md

https://github.com/pierre-chaville/automlk

https://medium.com/airbnb-engineering/listing-embeddings-for-similar-listing-recommendations-and-real-time-personalization-in-search-601172f7603e

https://github.com/keon/awesome-nlp

https://www.twosigma.com/insights/icml-2017-a-review-of-deep-learning-paperstalks-and-tutorials

https://www.twosigma.com/insights/25-of-our-favorite-papers-talks-presentations-and-workshops-from-nips-2017

https://github.com/kaz-Anova/StackNet

Richard Sutton - RL - an introduction

https://blog.jupyter.org/authoring-custom-jupyter-widgets-2884a462e724

https://arxiv.org/pdf/1802.10567.pdf

https://engineering.upside.com/a-beginners-guide-to-optimizing-pandas-code-for-speed-c09ef2c6a4d6

https://medium.com/s-c-a-l-e/google-systems-guru-explains-why-containers-are-the-future-of-computing-87922af2cf95

https://tryolabs.com/blog/2017/12/12/deep-learning-for-nlp-advancements-and-trends-in-2017/

https://www.twosigma.com/insights/25-of-our-favorite-papers-talks-presentations-and-workshops-from-nips-2017

https://www.twosigma.com/insights/icml-2017-a-review-of-deep-learning-paperstalks-and-tutorials

https://www.linkedin.com/pulse/deep-learning-ai-future-fabio-ciucci/

https://www.kdnuggets.com/2015/04/model-interpretability-neural-networks-deep-learning.html

https://people.csail.mit.edu/taolei/papers/emnlp16_rationale.pdf

https://www.alexirpan.com/2018/02/14/rl-hard.html

http://www.argmin.net/2018/01/25/optics/

https://www.quantamagazine.org/job-one-for-quantum-computers-boost-artificial-intelligence-20180129/

https://blog.openai.com/robust-adversarial-inputs/

https://blog.keras.io/the-limitations-of-deep-learning.html

https://blog.keras.io/the-future-of-deep-learning.html

https://berkeley-deep-learning.github.io/

http://nautil.us/issue/54/the-unspoken/why-a-hedge-fund-started-a-video-game-competition?utm_source=frontpage&utm_medium=mview&utm_campaign=why-a-hedge-fund-started-a-video-game-competition

https://arxiv.org/pdf/1710.04087.pdf

https://arxiv.org/pdf/1711.00043.pdf

https://arxiv.org/pdf/1711.00436.pdf

https://stats385.github.io/

https://www-wired-com.cdn.ampproject.org/c/s/www.wired.com/story/googles-ai-wizard-unveils-a-new-twist-on-neural-networks/amp

https://arxiv.org/pdf/1611.03530.pdf

https://www.quora.com/Why-is-the-paper-%E2%80%9CUnderstanding-Deep-Learning-Requires-Rethinking-Generalization%E2%80%9D-important

https://arxiv.org/pdf/1403.2229.pdf

https://papers.nips.cc/paper/5656-hidden-technical-debt-in-machine-learning-systems.pdf

http://rll.berkeley.edu/deeprlcourse/

http://icml.cc/2016/tutorials/deep_rl_tutorial.pdf

https://hackernoon.com/spotifys-discover-weekly-how-machine-learning-finds-your-new-music-19a41ab76efe

https://www.quantamagazine.org/new-theory-cracks-open-the-black-box-of-deep-learning-20170921/

https://arxiv.org/abs/1709.03856 - https://github.com/facebookresearch/Starspace

https://arxiv.org/abs/1406.2673

http://www.symmetrymagazine.org/article/neural-networks-meet-space

https://sites.google.com/site/vianneyperchet/mva

https://www.amazon.com/Nicholas-J.-Higham/e/B001JS5MHS/ref=dp_byline_cont_book_1