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1.【改变未来沟通方式的七项NLP技术】《The 7 NLP Techniques That Will Change How You Communicate in the Future (Part I)》By James Le

https://heartbeat.fritz.ai/the-7-nlp-techniques-that-will-change-how-you-communicate-in-the-future-part-i-f0114b2f0497

By 算法组

2.【面向推荐系统的机器学习】《Machine Learning for Recommender systems》by Pavel Kordík

Part 1(algorithms, evaluation and cold start)

https://medium.com/recombee-blog/machine-learning-for-recommender-systems-part-1-algorithms-evaluation-and-cold-start-6f696683d0ed

Part 2 (Deep Recommendation, Sequence Prediction, AutoML and Reinforcement Learning in Recommendation)

https://medium.com/recombee-blog/machine-learning-for-recommender-systems-part-2-deep-recommendation-sequence-prediction-automl-f134bc79d66b

PDF：https://pan.baidu.com/s/17r2Uvl8KzIJxcPY4MGpq2A#list/path=%2F

By 爱可可-爱生活

3.【Facebook AI产品规模化之道】《How Facebook scales AI | ZDNet》

https://www.zdnet.com/article/how-facebook-scales-ai/

By 爱可可-爱生活

4.【强化学习】Distributed Prioritized Experience Replay

本文是DeepMind发表于ICLR 2018的工作。Exploration是强化学习里面比较难的问题，这篇paper通过分布式，可以说用一个最简单的做法却实现了非常好的exploration。同时，这篇paper也让我们要意识到RL的分布式计算是非常重要的一个环节，不仅仅是加快训练速度，还可以更好的提升效果。

https://www.paperweekly.site/papers/1994

By PaperWeekly