Section 11: PCA
Jupyter Notebook Yujie Guo (2022), Artur Rego Costa (2021), Danylo Lavrentovich (2020), adapted from Dan Greenfield, Verena Volf, and James Xue from past years
This Friday in section we will try and work on our general understanding of PCA, as well as give practical pointers for interpreting its output.
- Quick Linear Algebra Review
- Derivation of PCA to show how covariance matrix and eigenvectors show up
- Generative Forms of PCA
- go through a Jupyter notebook [download][view]. where we use PCA to analyze handwritten digits, with surprising similarities to this week's PSet!