Probably the most complete machine learning and Python (including math) quick check table in history.

Novice Learning machine learning is very difficult, is to collect data is also very laborious. Fortunately, Robbie Allen collects the most comprehensive list of fast-track tables on machine learning, Python and related mathematics from various sources. Highly Recommended collection!

There are many aspects of machine learning. When I started to refresh the theme, I came across a variety of "quick look tables" that simply listed all the points of a given topic that needed to be known. Finally, I collected a quick look-up table related to machine learning. Some I often refer to and think that other people may also benefit from it. Therefore, this article on the internet I found a very good 27 fast-track table to share, for everyone's reference.

Machine Learning (machines learning)

There are a number of useful flowchart and machine learning algorithm tables. This includes only the most comprehensive quick-check tables found.

Neural network Architecture (Neuralnetwork architectures)

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

Microsoft Azure Algorithmic Flow Diagram ( Microsoft azurealgorithm Flowchart )

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

SAS Algorithmic Flowchart (SAS algorithm Flowchart)

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

Algorithm Summary (algorithmsummary)

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

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

Algorithmic Advantages and disadvantages (Algorithmpro/con)

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

Python

Of course python has a lot of online resources. For this section, only the best quick check tables that are encountered are included.

Algorithm (algorithms)

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

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

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

Mathematics (Math)

If you really want to learn about machine learning, then you need to lay a solid foundation for the understanding of statistics (especially probabilities), linear algebra, and calculus. I was a minor in mathematics during my undergraduate course, but I definitely need to review this knowledge. These quick look tables provide the math behind most of the most common machine learning algorithms that need to be understood.

Probability (probability)

Source:

Http://www.wzchen.com/s/probability_cheatsheet.pdf

Linear algebra (Linear Algebra)

Source:

Https://minireference.com/static/tutorials/linear_algebra_in_4_pages.pdf

Statistics (Statistics)

Source:

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

Calculus (Calculus)

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

If you want all the fast-track tables, I've moved the author's zip file containing all 27 quick-look tables into the wall. NET disk: Https://pan.baidu.com/s/1hs7n8LQ extract password: bvq1. Welcome to download!

Text reference: Click to read the full text is visible (need FQ).

"Network Cold", search "network cold" can pay attention to

Probably the most complete machine learning and Python (including math) quick check table in history.