> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/cuvs/llms.txt.
> For full documentation content, see https://docs.nvidia.com/cuvs/llms-full.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/cuvs/_mcp/server.

# Preprocessing Guide

Use these guides for cuVS preprocessing APIs that transform, compress, or project vectors before downstream search or analysis.

- [Binary Quantizer](/cuvs/user-guide/api-guides/preprocessing-guide/binary-quantizer): compress vectors into binary representations for compact storage and fast comparisons.
- [PCA](/cuvs/user-guide/api-guides/preprocessing-guide/pca): reduce dimensionality with a linear projection while preserving as much variance as possible.
- [Product Quantization](/cuvs/user-guide/api-guides/preprocessing-guide/product-quantization): split vectors into subvectors and encode each part with compact codebooks.
- [Scalar Quantizer](/cuvs/user-guide/api-guides/preprocessing-guide/scalar-quantizer): compress each vector dimension independently with scalar quantization.
- [Spectral Embedding](/cuvs/user-guide/api-guides/preprocessing-guide/spectral-embedding): create lower-dimensional embeddings from graph structure.