Resources for learning principal components analysis and dimension reduction

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- Making sense of principal components analysis, eigen vectors & eigenvalues (most popular stackoverflow explanation)
- Intuitive explanation for how PCA turns from a geometric problem to a linear algebra problem with eigenvectors (another popular stackoverflow question)

- Eigenvectors and eigenvalues
- Principal component analysis
- Essence of linear algebra series on YouTube (highly popular series with millions of views)

- An introduction to principal components with examples in R
- Dimension reduction with R workshop by Saskia Freytag
- An overview of principal components analysis in Python (freeCodeCamp)
- Brief tutorial I gave on multivariate EEG analysis with linear discriminant via generalized eigendecomposition (MATLAB)

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Text and figures are licensed under Creative Commons Attribution CC BY 4.0. Source code is available at https://github.com/hauselin/rtutorialsite, unless otherwise noted. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".

For attribution, please cite this work as

Lin (2019, Aug. 7). Data science: Resources for principal components analysis and dimension reduction. Retrieved from https://hausetutorials.netlify.com/posts/2019-10-07-resources-for-principal-components-analysis/

BibTeX citation

@misc{lin2019resources, author = {Lin, Hause}, title = {Data science: Resources for principal components analysis and dimension reduction}, url = {https://hausetutorials.netlify.com/posts/2019-10-07-resources-for-principal-components-analysis/}, year = {2019} }