There are many aspects to machine learning, and as I started researching it, I found all sorts of “cheat sheets” that succinctly list the key points for a given topic. I ended up with over 20 machine learning cheat sheets, some of which I read regularly and others that I learned a lot from. This article contains 27 cheat sheets I found on the Internet, so please let me know if I missed anything.

— Robbie Allen


Download most of the machine learning cheat sheets collected in this article by replying to “Cheat sheets” on wechat.



This article is authorized from Linux China (ID:linux-cn).


In this paper, the navigation

  • Machine learning 05%

    • Neural network architecture 07%

    • Microsoft Azure algorithm flow chart 10%

    • SAS algorithm flow chart 14%

    • Algorithm summary

    • Advantages and disadvantages of the algorithm 26%

  • Python 30%

    • Algorithm is 31%

    • Python based 35%

    • Numpy 41%

    • Pandas 52%

    • Matplotlib 61%

    • Scikit Learn 68%

    • Tensorflow 77%

    • Pytorch 81%

  • 84% of mathematics

    • The probability of 86%

    • Linear algebra 90%

    • 93% of statistics

    • Calculus 97%


Machine learning

Here are some useful flowcharts and tables of machine learning algorithms, but I’ve included only the most comprehensive ones I’ve found.


Neural network architecture

(via:http://www.asimovinstitute.org/neural-network-zoo/)



Neural network park


Microsoft Azure algorithm flow chart

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



Machine learning algorithms for Microsoft Azure Machine Learning Studio


Flow chart of SAS algorithm

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



SAS: Which machine learning algorithm should I use?


Algorithm is summarized

(via:http://machinelearningmastery.com/a-tour-of-machine-learning-algorithms/)



Guide to machine learning algorithms

(via:http://thinkbigdata.in/best-known-machine-learning-algorithms-infographic/)



What is the best known machine learning algorithm?


algorithm

(via: https://blog.dataiku.com/machine-learning-explained-algorithms-are-your-friend)




Python

Naturally, there are many online resources for Python, and in this section I’ve included only the best cheat sheets I’ve seen.



algorithm

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





Python based

(via:http://datasciencefree.com/python.pdf)



Data science Python cheat sheet for getting started

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




NumPy Cheat Sheet – Python for Data Science

(via:https://www.dataquest.io/blog/numpy-cheat-sheet/)



Numpy Cheat Sheet

(via: http://datasciencefree.com/numpy.pdf)




NumPy Cheat Sheet: Data Analysis in Python

(via:https://www.datacamp.com/community/blog/python-numpy-cheat-sheet#gs.Nw3V6CE)




Data-Science-Ipython-Notebooks(NumPy)

(via:https://github.com/donnemartin/data-science-ipython-notebooks/blob/master/

numpy/numpy.ipynb)




Data Analysis with Pandas

(via:http://datasciencefree.com/pandas.pdf)




Pandas Cheat Sheet for Data Science in Python

(via:https://www.datacamp.com/community/blog/python-pandas-cheat-sheet#gs.

S4P4T=U)




Data-Science-Ipython-Notebooks(Pandas)

(via:https://github.com/donnemartin/data-science-ipython-notebooks/blob/master/

pandas/pandas.ipynb)




Matplotlib Cheat Sheet: Plotting in Python

(via:https://www.datacamp.com/community/blog/python-matplotlib-cheat-sheet)



Data-Science-Ipython-Notebooks

(via: https://github.com/donnemartin/data-science-ipython-notebooks/blob/master/

matplotlib/matplotlib.ipynb)




Scikit Learn

(via: https://www.datacamp.com/community/blog/scikit-learn-cheat-sheet#gs.fZ2A1Jk)





Machine Learning Cheat Sheet (for scikit-learn)

(via:http://peekaboo-vision.blogspot.de/2013/01/machine-learning-cheat-sheet-for-scikit.html)





ml_cheat_sheet

(via: https://github.com/rcompton/ml_cheat_sheet/blob/master/supervised_learning.

ipynb)





TensorFlow-Examples

(via: https://github.com/aymericdamien/TensorFlow-Examples/blob/

master/notebooks/1_Introduction/basic_operations.ipynb)




Pytorch Cheatsheet

(via: https://github.com/bfortuner/pytorch-cheatsheet)




mathematics

If you want to understand machine learning, you’ll need a thorough understanding of statistics (especially probability), linear algebra, and some calculus. I minored in math as an undergraduate, but I really need to brush up. These cheat sheets provide most of the math you need to know behind machine learning algorithms.



The probability of

(via:http://www.wzchen.com/s/probability_cheatsheet.pdf)



Probability cheat sheet 2.0



Linear algebra

(via: https://minireference.com/static/tutorials/linear_algebra_in_4_pages.pdf)



Linear algebra explained in four pages


statistical

(via: http://web.mit.edu/~csvoss/Public/usabo/stats_handout.pdf)



Statistics cheat sheet


Differential and integral calculus

(via:http://tutorial.math.lamar.edu/getfile.aspx?file=B,41,N)



Calculus cheat sheet


Original address:

https://unsupervisedmethods.com/cheat-sheet-of-machine-learning-and-python-and-math-cheat-sheets-a4afe4e791b6