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

# Machine learning and deep learning

Data Science & AI Workbench facilitates machine learning and deep learning by enabling you to [develop models](https://anaconda.com/docs/data-science/latest/data-science-workflows/ml-deep-learn/dev-model.md), [train them](https://anaconda.com/docs/data-science/latest/data-science-workflows/ml-deep-learn/train-model.md), and [deploy them](https://anaconda.com/docs/data-science/latest/data-science-workflows/ml-deep-learn/deploy-model.md). You can also use Workbench to [query and score models](https://anaconda.com/docs/data-science/latest/data-science-workflows/ml-deep-learn/query-score-model.md) that have been [deployed as a REST API](https://anaconda.com/docs/data-science/latest/data-science-workflows/deployments/rest-api.md).

To help get you started, Workbench includes several sample notebooks for common repetitive tasks. You can access them from the gallery of Sample Projects available from **Projects**. See [Projects](https://anaconda.com/docs/data-science/latest/data-science-workflows/projects/main.md) for more information.

We’ve also provided a walkthrough of the process for [creating an interactive data visualization](https://anaconda.com/docs/data-science/latest/data-science-workflows/viz.md).