> ## Documentation Index
> Fetch the complete documentation index at: https://docs.graphext.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Embed

| Step                                                                      | Fast | Description                                                                                         |
| ------------------------------------------------------------------------- | ---- | --------------------------------------------------------------------------------------------------- |
| [embed\_dataset](/api-docs/analyse/embed/embed_dataset)                   |      | Reduce the dataset to an n-dimensional numeric vector embedding                                     |
| [embed\_images](/api-docs/analyse/embed/embed_images)                     |      | Embed images using pretrained DL models                                                             |
| [embed\_items](/api-docs/analyse/embed/embed_items)                       |      | Trains an *item2vec* model on provided lists of items (or sentences of words, etc.)                 |
| [embed\_sessions](/api-docs/analyse/embed/embed_sessions)                 |      | Trains an *item2vec* model on provided lists of items                                               |
| [embed\_text](/api-docs/analyse/embed/embed_text)                         |      | Parse and calculate a (word-averaged) embedding vector for each text                                |
| [embed\_text\_with\_model](/api-docs/analyse/embed/embed_text_with_model) |      | Use language models to calulate an embedding for each text in provided column                       |
| [embed\_with\_trees](/api-docs/analyse/embed/embed_with_trees)            |      | Reduce the dataset to an n-dimensional numeric vector embedding using a Forest model's tree indices |
| [layout\_dataset](/api-docs/analyse/embed/layout_dataset)                 |      | Reduce the dataset to 2 dimensions that can be mapped to x/y node positions                         |
| [vectorize\_dataset](/api-docs/analyse/embed/vectorize_dataset)           |      | Create a vectorized (numeric) dataset, (optionally) of reduced dimensionality                       |