【最全资源】关于机器学习的干货借鉴

主要是为了汇总讲的比较好的一些论文或博客。

1、SVD分解和PCA降维等问题

http://blog.csdn.net/zhongkejingwang/article/details/42264479（这个写的不错）

http://www.cnblogs.com/LeftNotEasy/archive/2011/01/08/lda-and-pca-machine-learning.html

http://datartisan.com/article/detail/217.html

2、决策树：

https://www.analyticsvidhya.com/blog/2016/04/complete-tutorial-tree-based-modeling-scratch-in-python/

https://www.analyticsvidhya.com/blog/2016/03/complete-guide-parameter-tuning-xgboost-with-codes-python/

决策树调参

http://www.jianshu.com/p/f9b070e42b0e

3、数据挖掘

http://www.leiphone.com/news/201703/kCMQyffeP0qUgD9a.html

http://www.leiphone.com/news/201611/MfAvK0oVL9Qkes3G.html

https://www.kaggle.com/wiki/Home（kaggle官方的一些信息）

https://uqer.io/community/share/54d83bb3f9f06c276f651a6e

https://www.huxiu.com/article/175046/1.html?f=member_article（面试问题）

http://staticor.io/（这个博客不错）

4、正则表达式

http://deerchao.net/tutorials/regex/regex.htm

5、python包地址

http://www.lfd.uci.edu/~gohlke/pythonlibs/

https://pypi.python.org/pypi/opencv-python

6.深度学习

https://zhuanlan.zhihu.com/p/21930884

https://mp.weixin.qq.com/s?__biz=MzAwMjM3MTc5OA==&mid=402156285&idx=1&sn=13275b8f4ec46c901290c66c6c0ffa28&utm_source=tuicool&utm_medium=referral

http://speech.ee.ntu.edu.tw/~tlkagk/courses_ML17.html

http://blog.csdn.net/heyongluoyao8/article/details/48636251

http://tensorfly.cn/tfdoc/mltools.html

http://colah.github.io/

https://www.nature.com/nature/journal/v521/n7553/pdf/nature14539.pdf

https://r2rt.com/index2.html

RNN基础 : http://colah.github.io/posts/2015-08-Understanding-LSTMs/ 

https://r2rt.com/written-memories-understanding-deriving-and-extending-the-lstm.html

7、github

http://www.worldhello.net/gotgithub/

原文转自：https://blog.csdn.net/baidu_36557924/article/details/79519371