- Decoding Dimensionality Reduction, PCA and SVD
- Relationship between SVD and PCA. How to use SVD to perform PCA?
- Why Octave, R, Numpy, and LAPACK yield different SVD results on the same matrix
- “Normalizing” variables for SVD / PCA
- Numpy seems to produce incorrect eigenvectors
- Why we need to normalize data before analysis
- Why standardize the matrix columns before SVD?
- Understand Complex Datasets, Data Mining with Matrix Decompositions
- SVD code with Python and R
- dimensionality reduction -- general sense of the terms used in the lecture
- Low-rank approximation of a matrix
- Singular Value Decomposition of General Matrices