机器学习中值得反复翻阅的小抄20+

写在前面:

机器学习(Machine Learning)有很多方面,本文中网罗的是这个学习领域中各种各样的“小抄”,它们简明扼要地列出了给定主题的关键知识点,正在进行机器学习的小伙伴可以保存下来,在平时的学习中进行翻阅查询,文末附详细资源获取方式。

PART1:流程图+机器学习算法表

神经网络架构

来源:http://www.asimovinstitute.org/neural-network-zoo/

微软Azure算法流程图

来源:https://docs.microsoft.com/en-us/azure/machine-learning/machine-learning-algorithm-cheat-sheet

SAS算法流程图

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

算法总结

来源:http://machinelearningmastery.com/a-tour-of-machine-learning-algorithms/

机器学习算法指引

来源:http://thinkbigdata.in/best-known-machine-learning-algorithms-infographic/

算法优劣

来源:https://blog.dataiku.com/machine-learning-explained-algorithms-are-your-friend

PART2:Python

算法

来源:https://www.analyticsvidhya.com/blog/2015/09/full-cheatsheet-machine-learning-algorithms/

Python基础

来源1:http://datasciencefree.com/python.pdf

来源2:https://www.datacamp.com/community/tutorials/python-data-science-cheat-sheet-basics#gs.0x1rxEA

Numpy

来源1:https://www.dataquest.io/blog/numpy-cheat-sheet/

来源2:http://datasciencefree.com/numpy.pdf

来源3:https://www.datacamp.com/community/blog/python-numpy-cheat-sheet#gs.Nw3V6CE

来源4:https://github.com/donnemartin/data-science-ipython-notebooks/blob/master/numpy/numpy.ipynb

Pandas

来源1:http://datasciencefree.com/pandas.pdf

来源2:https://www.datacamp.com/community/blog/python-pandas-cheat-sheet#gs.S4P4T=U

来源3:https://github.com/donnemartin/data-science-ipython-notebooks/blob/master/pandas/pandas.ipynb

Matplotlib

来源1:https://www.datacamp.com/community/blog/python-matplotlib-cheat-sheet

来源2:https://github.com/donnemartin/data-science-ipython-notebooks/blob/master/matplotlib/matplotlib.ipynb

Scikit Learn

来源1:https://www.datacamp.com/community/blog/scikit-learn-cheat-sheet#gs.fZ2A1Jk

来源2:http://peekaboo-vision.blogspot.de/2013/01/machine-learning-cheat-sheet-for-scikit.html

来源3:https://github.com/rcompton/ml_cheat_sheet/blob/master/supervised_learning.ipynb

TensorFlow

来源:https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/1_Introduction/basic_operations.ipynb

Pytorch

来源:https://github.com/bfortuner/pytorch-cheatsheet

PART3:数学

概率

来源:http://www.wzchen.com/s/probability_cheatsheet.pdf

线性代数

来源:https://minireference.com/static/tutorials/linear_algebra_in_4_pages.pdf

统计学

来源:http://web.mit.edu/~csvoss/Public/usabo/stats_handout.pdf

微积分

注|内容来源“51CTO”

网址:http://ai.51cto.com/art/201804/571607.htm#topx

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