Comprehensive Collection of Machine Learning, Python, and Mathematics Cheat Sheets

Machine Learning

The author gathered more than 20 machine‑learning cheat sheets found online, many of which are revisited frequently; this article presents 27 of them as of June 1 2017.

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

SAS Algorithm Flowchart

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/

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

Algorithm Pros and Cons

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

Python

Numerous online resources provide concise cheat sheets for Python data‑science tools; the following are the most useful collected by the author.

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://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-ipynb.../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/.../basic_operations.ipynb

PyTorch

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

Mathematics

Understanding machine learning also requires solid foundations in statistics (especially probability), linear algebra, and calculus; the following cheat sheets cover the essential mathematical concepts.

Probability

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

Linear Algebra

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

Statistics

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

Calculus

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

Author: Robbie Allen (translator: wxy)

Source: https://linux.cn/article-8754-1.html

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