machine-learning
PCA: variance maximization and reconstruction error
taught
Finding the directions of greatest variance in data, provably equivalent to minimizing reconstruction error.
Taught in
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PCA: two views of the same idea
Modern Machine Learning
Requires
- data-as-vectors-and-matrices required
Required by
- Modern embeddings and semantic search required
- Running PCA in practice required
- t-SNE and UMAP required
Local knowledge map
Local knowledge map
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