# PCA

- Page: https://shared.btbytes.com/p/pca
- Date: 2023-04-14
- Tags: machine-learning

Principal Component Analysis is mostly commonly used for dimensionality reduction.

It is a data preperation technique performed on data prior to modeling. After data cleaning and data scaling and before training a predictive model.

[A tutorial on Principal Components Analysis](http://web.archive.org/web/20151006155533/http://www.cs.otago.ac.nz/research/publications/OUCS-2002-12.pdf) -- a technical report with code in scilab.

[Implementing a Principal Component Analysis (PCA)](https://sebastianraschka.com/Articles/2014_pca_step_by_step.html) in Python, step by step by [Sebastian Raschka](https://sebastianraschka.com), who has written [Machine learning and AI beyond the basics](https://sebastianraschka.com/books/)