Cheat Sheet of Machine Learning and Python (and Math) Cheat Sheets

Published in

Machine Learning in Practice

4 min readJun 1, 2017

If you like this article, check out another by Robbie:
My Curated List of AI and Machine Learning Resources

There are many facets to Machine Learning. As I started brushing up on the subject, I came across various “cheat sheets” that compactly listed all the key points I needed to know for a given topic. Eventually, I compiled over 20 Machine Learning-related cheat sheets. Some I reference frequently and thought others may benefit from them too. This post contains 27 of the better cheat sheets I’ve found on the web. Let me know if I’m missing any you like.

Given how rapidly the Machine Learning space is evolving, I imagine these will go out of date quickly, but at least as of June 1, 2017, they are pretty current.

If you want all of the cheat sheets without having to download them individually like I did, I created a zip file containing all 27. Enjoy!

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Machine Learning

There are a handful of helpful flowcharts and tables of Machine Learning algorithms. I’ve included only the most comprehensive ones I’ve found.

Neural Network Architectures

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

Microsoft Azure Algorithm Flowchart

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

Machine learning algorithm cheat sheet 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/

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

Which are the best known machine learning algorithms?

Algorithm Pro/Con

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

Python

Unsurprisingly, there are a lot of online resources available for Python. For this section, I’ve only included the best cheat sheets I’ve come across.

Algorithms

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

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

Scikit Learn

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

Source: http://peekaboo-vision.blogspot.de/2013/01/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 really want to understand Machine Learning, you need a solid understanding of Statistics (especially Probability), Linear Algebra, and some Calculus. I minored in Math during undergrad, but I definitely needed a refresher. These cheat sheets provide most of what you need to understand the Math behind the most common Machine Learning algorithms.