机器学习无从下手？整理的这些清单可以助你一臂之力！

数据挖掘流程

source：https://github.com/FavioVazquez/ds-cheatsheets

此网址还提供了其他众多涉及数学科学的cheat sheet，非常推荐

算法的选择

source: https://scikit-learn.org/stable/tutorial/machine_learning_map/

source：https://blogs.sas.com/content/subconsciousmusings/2017/04/12/machine-learning-algorithm-use/

source：https://hackernoon.com/choosing-the-right-machine-learning-algorithm-68126944ce1f

SIGAI算法地图

source: http://www.tensorinfinity.com/paper_18.html

sklearn使用

source：https://www.datacamp.com/community/data-science-cheatsheets

此网页也提供了numpy,pandas, matplotlib,PySpark,Keras等module的使用方法

有监督学习

source: https://github.com/afshinea/stanford-cs-229-machine-learning

无监督学习

source: https://github.com/afshinea/stanford-cs-229-machine-learning

模型评估指标

source: http://www.damienfrancois.be/blog/files/modelperfcheatsheet.pdf

更多关于数据科学的cheat sheet，可以参考：

• https://github.com/FavioVazquez/ds-cheatsheets
• https://github.com/soulmachine/machine-learning-cheat-sheet
• https://www.analyticsvidhya.com/blog/2017/02/top-28-cheat-sheets-for-machine-learning-data-science-probability-sql-big-data/
• https://medium.com/machine-learning-in-practice/cheat-sheet-of-machine-learning-and-python-and-math-cheat-sheets-a4afe4e791b6
• https://static.coggle.it/diagram/WHeBqDIrJRk-kDDY/t/categories-of-algorithms-non-exhaustive