Ultimate Machine Learning Cheat Sheet: Algorithms, Python Tools & Math Essentials

Machine Learning

I have gathered more than 20 machine‑learning cheat sheets, totaling 27 concise reference sheets that list key concepts and algorithms. The collection was assembled in 2017 and remains a handy resource for quick review.

Neural Network Architectures

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

Microsoft Azure Algorithm Cheat Sheet

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

SAS Algorithm Cheat Sheet

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

Algorithm Summary

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

Best‑Known Machine Learning Algorithms (Infographic)

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

Algorithm Pros & Cons

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

Python

Below are the best‑rated Python cheat sheets I have found, covering algorithms, core language basics, NumPy, Pandas, Matplotlib, Scikit‑Learn, TensorFlow, and PyTorch.

Algorithms

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

Python Basics

Source: http://datasciencefree.com/python.pdf

NumPy

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

Pandas

Source: http://datasciencefree.com/pandas.pdf

Matplotlib

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

Scikit‑Learn

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

TensorFlow

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

PyTorch

Source: https://github.com/bfortuner/pytorch-cheatshee

Mathematics

Understanding machine learning also requires solid knowledge of probability, linear algebra, statistics, and calculus. The following cheat sheets provide concise overviews of these mathematical foundations.

Probability

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

Linear Algebra

Source: https://minireference.com/static/tutorials/linear_algebra_in_4_pages.pd

Statistics

Source: http://web.mit.edu/~csvoss/Public/usabo/stats_handout.pd

Calculus

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