动手学习机器学习

Learning from data

sklearn and tensorflow practices

ML

https://github.com/ujjwalkarn/Machine-Learning-Tutorials

tensorfolw:

https://github.com/aymericdamien/TensorFlow-Examples

https://machinelearningmastery.com/start-here/

NLP and deep learning

http://web.stanford.edu/class/cs224n/

https://github.com/adventuresinML/adventures-in-ml-code

https://github.com/pangolulu/rnn-from-scratch

https://github.com/pangolulu/neural-network-from-scratch

分层softmax

https://kiddie92.github.io/2019/06/15/%E5%88%86%E5%B1%82softmax/

http://hemingwang.blogspot.com/2019/04/word2vec.html

笔记

https://coggle.it/diagram/XXIxd7Ml_i_-r37F/t/word2vec%E7%AC%94%E8%AE%B0

word2vec 数学原理

http://www.ipaomi.com/2017/09/22/word2vec-%E6%95%B0%E5%AD%A6%E5%8E%9F%E7%90%86/

https://shomy.top/2017/07/28/word2vec-all/

Word2Vec Resources

https://github.com/clulab/nlp-reading-group/wiki/Word2Vec-Resources

word2vec Parameter Learning Explained Xin Rong ronxin@umich.edu

https://arxiv.org/pdf/1411.2738.pdf

word2vec Parameter Learning Explained 中文

https://blog.csdn.net/lanyu_01/article/details/80097350

CBOW（continuous bag-of-word）模型和SG（skip-gram）模型，以及两种参数优化技术：hierarchical softmax 和 negative sampling.

LDA