机器学习人工学weekly-2018/6/10

1. MIT脑科学课程视频，虽然跟工程不太一样，但是cognitive science也是很重要

MIT 9.11: The Human Brain (Spring 2018) (mit.edu)

链接：https://nancysbraintalks.mit.edu/course/9-11-the-human-brain

2. 阿里巴巴用虚拟淘宝做RL

Virtual-Taobao: Virtualizing Real-world Online Retail Environment for Reinforcement Learning

链接：https://arxiv.org/abs/1805.10000?utm_campaign=ARCHITECHT&utm_medium=email&utm_source=ARCHITECHT_31

3. 周志华团队的multi-layer GDBT

Multi-Layered Gradient Boosting Decision Trees

链接：https://arxiv.org/pdf/1806.00007.pdf

4. object detection算法详解

UNDERSTANDING DEEP LEARNING FOR OBJECT DETECTION

链接：http://zoey4ai.com/2018/05/12/deep-learning-object-detection/

5. tSNE在TF.js里的快速实现

Realtime tSNE Visualizations with TensorFlow.js

链接：https://ai.googleblog.com/2018/06/realtime-tsne-visualizations-with.html

6. 苹果宣布Create ML项目

链接：https://developer.apple.com/documentation/create_ml

7. 自动feature engineering（这个为啥不能搞AutoML?）

Automated Feature Engineering in Python

链接：https://towardsdatascience.com/automated-feature-engineering-in-python-99baf11cc219

8. RL快速介绍，写的还行

Reinforcement Learning from scratch

链接：https://blog.insightdatascience.com/reinforcement-learning-from-scratch-819b65f074d8

9. 攻击机器学习模型

Attacks against machine learning — an overview

链接：https://elie.net/blog/ai/attacks-against-machine-learning-an-overview

10. 各种学习资料

10.1 Georgia Tech NLP课程资料

链接：https://github.com/jacobeisenstein/gt-nlp-class

10.2 RL各种算法PyTorch实现

链接：https://github.com/higgsfield/RL-Adventure-2

10.3 data science for startups小书

链接：https://towardsdatascience.com/data-science-for-startups-blog-book-bf53f86ca4d5

10.4 挺好的一本机器学习的小书

链接：http://ciml.info/