好文章

看名字就知道很重要的网站

https://paperswithcode.com/

讲述Random Forest的好文章

https://www.guru99.com/r-random-forest-tutorial.html#2

R的特征工程

http://www.shareditor.com/blogshow?blogId=106

 https://zhuanlan.zhihu.com/p/25732304

设计模式

https://cloud.tencent.com/developer/article/1330380

 

机器学习的评估

http://www.javashuo.com/article/p-sqqodhsa-ke.html

数据仓库

http://www.javashuo.com/article/p-tnhnyinf-ca.html

https://www.jianshu.com/p/849db358ec61

https://www.jianshu.com/p/b635a3073e7b

算法

https://github.com/MisterBooo/LeetCodeAnimation

https://github.com/azl397985856/leetcode

 tensorflow

http://www.elecfans.com/rengongzhineng/635154.html#http://bbs.elecfans.com

关于Lasso和岭回归

http://www.javashuo.com/article/p-mwrwndzg-hd.html

 https://blog.csdn.net/JH_Zhai/article/details/82694937

 

Accnture

https://employeereferralprogram.accenture.com/#/index

 

http://www.blogjava.net/hh-lux/archive/2006/12/10/86635.html

https://blog.csdn.net/u010142437/article/details/26681213

 

特征工程

https://www.zhihu.com/question/29316149

http://www.cnblogs.com/jasonfreak/p/5448462.html

http://www.javashuo.com/article/p-cfovaxvj-ky.html

http://www.javashuo.com/article/p-gtevaphc-de.html

 

关于向量机的文章

https://blog.csdn.net/v_JULY_v/article/details/7624837

http://blog.pluskid.org/?page_id=683

 

关于PCA以及白化的好文章（一个英文版，一个中文版）

http://ufldl.stanford.edu/wiki/index.php/UFLDL_Tutorial

http://ufldl.stanford.edu/wiki/index.php/UFLDL%E6%95%99%E7%A8%8B

 

PCA系列好文

https://blog.csdn.net/baimafujinji/article/details/50372906

https://blog.csdn.net/baimafujinji/article/details/50373143

https://blog.csdn.net/baimafujinji/article/details/79372911

 

 BAT机器学习面试1000题

https://blog.csdn.net/v_JULY_v/article/details/78121924

 

关于YARN的fair

 http://blog.cloudera.com/blog/2018/06/yarn-fairscheduler-preemption-deep-dive/

 

spark和es结合作聚类学习

https://code.i-harness.com/zh-CN/q/1b0ead4

 

争取天天读一篇的好博客，关于机器学习的

https://blog.csdn.net/lyl771857509/article/list/1?t=1

 

 python-Levenshtein类似度（距离）计算

https://blog.csdn.net/dcrmg/article/details/79228589

https://github.com/xiashiwendao/Metis/tree/master/docs 织云开源网址，个人fork

 

写给程序员的数据挖掘

http://guidetodatamining.com/

 

特征工程

https://www.zhihu.com/question/29316149

 

Python机器学习实践与Kaggle实战

 https://mlnote.wordpress.com/2015/12/16/python%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E5%AE%9E%E8%B7%B5%E4%B8%8Ekaggle%E5%AE%9E%E6%88%98-machine-learning-for-kaggle-competition-in-python/

 

机器学习资源（持续更新）

https://blog.csdn.net/linxid/article/details/83865649

吴恩达视频笔记

 https://github.com/fengdu78/Coursera-ML-AndrewNg-Notes

https://study.163.com/course/courseMain.htm?courseId=1004570029&_trace_c_p_k2_=907d8e659c5e47d5939d46f4627d14bb

 https://scikit-learn.org/stable/

华校专的我的网页

 http://www.huaxiaozhuan.com/

 

关于时间序列

https://zhuanlan.zhihu.com/p/21781849

https://blog.csdn.net/shanguier/article/details/77575565

https://tsfresh.readthedocs.io/en/latest/ 

https://www.jianshu.com/p/4130bac8ebec 简书的一个ARIMA的例子

 

Apriori算法

https://www.cnblogs.com/90zeng/p/apriori.html

https://www.cnblogs.com/dm-cc/p/5737147.html

机器学习的好博客（apriori的python3实现就是在这里找到的）

https://adataanalyst.com/tag/machine-learning/

 

ELK

grok的模式解析库
https://github.com/logstash-plugins/logstash-patterns-core/tree/master/patterns 或

https://github.com/thekrakken/java-grok/blob/master/src/main/resources/patterns/patterns
ELK面试题：https://mp.weixin.qq.com/s/iay2B4XGl5MuEqRBWqoipA

 

在线juypter

微软的

https://docs.microsoft.com/en-us/azure/notebooks/quickstart-create-share-jupyter-notebook

MyBinder

https://mybinder.org/

一篇介绍在线jupyter的简书文章

https://www.jianshu.com/p/e009997ab5d8