Machine Learning has many facets, and when I started researching to learn it, I came across all sorts of "cheat sheets" that succinctly list the key takeaways from a given topic. I ended up putting together over 20 machine learning related cheat sheets, some of which I flip through regularly and others that I have benefited from. This post contains 27 cheat sheets I found online, if you find anything I've missed, please let me know.
Changes in the field of machine learning are fast and I think these may be outdated soon, but at least for now, they are still trendy.
machine learning
Here are some useful flowcharts and tables of machine learning algorithms, and I've only included the most comprehensive ones I've found.
Neural Network Architecture
Neural Network Park
Microsoft Azure Algorithm Flowchart
Source: https://docs.microsoft.com/en-us/azure/machine-learning/machine-learning-algorithm-cheat-sheet
Machine Learning Algorithms for Microsoft Azure Machine Learning Studio
SAS algorithm flowchart
Source: http://blogs.sas.com/content/subconsciousmusings/2017/04/12/machine-learning-algorithm-use/
SAS: Which machine learning algorithm should I use?
Algorithm Summary
Source: http://machinelearningmastery.com/a-tour-of-machine-learning-algorithms/
Guide to Machine Learning Algorithms
Source: http://thinkbigdata.in/best-known-machine-learning-algorithms-infographic/
Which is the best known machine learning algorithm?
Algorithms Pros and Cons
Source: https://blog.dataiku.com/machine-learning-explained-algorithms-are-your-friend
Python
Naturally, there are also many online resources for Python, and in this section, I've included only the best cheat sheets I've seen.
algorithm
Source: https://www.analyticsvidhya.com/blog/2015/09/full-cheatsheet-machine-learning-algorithms/
Python Basics
Source: http://datasciencefree.com/python.pdf
Source: https://www.datacamp.com/community/tutorials/python-data-science-cheat-sheet-basics#gs.0x1rxEA
Numpy
Source: https://www.dataquest.io/blog/numpy-cheat-sheet/
Source: http://datasciencefree.com/numpy.pdf
Source: https://www.datacamp.com/community/blog/python-numpy-cheat-sheet#gs.Nw3V6CE
Source: https://github.com/donnemartin/data-science-ipython-notebooks/blob/master/numpy/numpy.ipynb
Pandas
Source: http://datasciencefree.com/pandas.pdf
Source: https://www.datacamp.com/community/blog/python-pandas-cheat-sheet#gs.S4P4T=U
Source: https://github.com/donnemartin/data-science-ipython-notebooks/blob/master/pandas/pandas.ipynb
Matplotlib
Source: https://www.datacamp.com/community/blog/python-matplotlib-cheat-sheet
来源： https://www.baohuayule.net .com/ www.baohuayule.com donnemartin/data-science- www.yisengyuLe.com ipython-notebooks/blob/master/ www.vboyule.cn matplotlib/matplotlib.ipynb
Scikit Learn
Source: https://www.datacamp.com/community/blog/scikit-learn-cheat-sheet#gs.fZ2A1Jk
Source: http://peekaboo-www.feifanyule.cn vision. www.boshenyl.cn blogspot.de/2013/01 www.taohuayuan178.com/machine-learning-cheat-sheet-for-scikit.html
Source: https://github.com/rcompton/ml_cheat_sheet/blob/master/supervised_learning.ipynb
Tensorflow
Source: https://github.com/aymericdamien/TensorFlow-Examples/blob/master/notebooks/1_Introduction/basic_operations.ipynb
Pytorch
Source: https://github.com/bfortuner/pytorch-cheatsheet
math
If you want to understand machine learning, you need a thorough understanding of statistics (especially probability), linear algebra, and some calculus. I minored in math as an undergraduate, but I do need a refresher. These cheat sheets provide most of the math you need to know behind machine learning algorithms.
probability
Source: http://www.wzchen.com/s/probability_cheatsheet.pdf
Probability Cheat Sheet 2.0
Linear Algebra
Source: https://minireference.com/static/tutorials/linear_algebra_in_4_pages.pdf
Explain linear algebra in four pages
statistics
Source: http://web.mit.edu/~csvoss/Public/usabo/stats_handout.pdf
Statistics Cheat Sheet
calculus
Source: http://tutorial.math.lamar.edu/getfile.aspx?file=B,41,N