26-lms-embeddings.qmd

# Word Embeddings {#sec-lms-embeddings}

## Objectives

- Understanding what are word embeddings
- Methods: `word2vec`, `doc2vec`, GLoVe, SVD/LSA
- Constructing a feature-co-occurrence matrix
- Fitting a word embedding model
- Using pre-trained embedding scores with documents
- Prediction based on embeddings
- Further methods

## Methods

Applicable methods for the objectives listed above.

## Examples

Examples here.

## Issues

Issues here.

## Further Reading

Additional resources from libraries or the web.

## Exercises

Add some here.