Cheat sheets for machine learning and programming
Collect useful cheat sheet resources for machine learning, deep learning, and programming languages (Python/R/Matlab).
1. Programming languages cheat sheets
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A site named Mathesaurus provides quick references for switching among Python/R/Matlab
for numeric processing and data visualization, etc. E.g., R for Matlab users, NumPy for R/Matlab users, etc.
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Scipy.org has documentations about “NumPy for Matlab users”.
1.1 R cheat sheets
- This site (RStudio resources) contains many useful cheat sheets for R and its packages.
E.g., base R, advanced R, data import/transformation for R,
Sparklyr package for Apache Spark, Keras, R Markdown, and ggplot2, etc.
2. Machine learning cheat sheets
- A GitHub repository gives cheat sheets of some commonly used Python/R packages/libraries
for machine learning and deep learning. The cheat sheets include:
- Tensorflow, Keras,
Neural Networks Zoo, Numpy, Scipy,
Pandas-1,
Pandas-2,
Pandas-3,
Scikit-learn,
Matplotlib,
ggplot2-1,
ggplot2-2,
PySpark,
PySpark-RDD,
PySpark-SQL,
R Studio(dplyr & tidyr)-1,
R Studio(dplyr & tidyr)-2,
Neural Network Cells,
Neural Network Graphs,
Deep Learning Cheat Sheet,
All Cheat Sheets(PDF),
last updated: June 2017
