Todos:
- book clustering: best seller in 2014 on tiki
- tony buoi sang: topic modeling
Must read:
- http://www.eecs.tufts.edu/~dsculley/papers/Detecting_Adversarial_Advertisements.pdf
- http://blog.echen.me/2011/04/27/choosing-a-machine-learning-classifier/
- https://github.com/fabianp/minirank/blob/master/notebooks/pairwise_transform.ipynb
- http://machinelearningmastery.com/tactics-to-combat-imbalanced-classes-in-your-machine-learning-dataset/
Curated:
- http://www.kdnuggets.com/2014/08/kdd-2014-awards-winners.html
- http://blog.david-andrzejewski.com/machine-learning/practical-machine-learning-tricks-from-the-kdd-2011-best-industry-paper/
- http://www.fi.muni.cz/usr/sojka/posters/rehurek-sojka-scipy2011.pdf
- http://www.slideshare.net/hustwj/cikm-keynotenov2014
- http://deepdist.com/
- http://moviemood.co/basic
- http://datagenetics.com/blog.html
- http://nbviewer.ipython.org/url/norvig.com/ipython/Probability.ipynb
- http://ufldl.stanford.edu/tutorial/supervised/SoftmaxRegression/
- https://blog.rjmetrics.com/2015/09/30/the-ultimate-guide-to-data-science-blogs-150-and-counting/
Cool blogs:
- http://www.eecs.tufts.edu/~dsculley
- http://blog.echen.me/2011/04/27/choosing-a-machine-learning-classifier/
- https://github.com/zygmuntz?tab=repositories
- http://blog.csdn.net/u010693617/article/details/9148747
- http://www.lucypark.kr/courses/2015-ba/text-mining.html#topic-modeling
- http://karpathy.github.io/
- http://bugra.github.io/
- http://colah.github.io/
- http://linanqiu.github.io/2015/05/20/word2vec-sentiment/
- http://multithreaded.stitchfix.com/blog/2015/03/11/word-is-worth-a-thousand-vectors/
- http://blog.yhathq.com/
- http://www.gregreda.com/
- http://radimrehurek.com/gensim/models/phrases.html
- http://fa.bianp.net/
Visualizations:
Writing: