> ## 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.

# Training models

Anaconda Enterprise provides machine learning libraries such as scikit-learn and Tensorflow that you can use to train the models you create.

## To train a model

When you are ready to run an algorithm against your model and tune it, download the `scikit-learn` or `Tensorflow` package from the `anaconda` channel. If you don’t see this channel or these packages in your **Channels** list, contact your Administrator to [mirror these packages](../../admin/chan-pkg/mirror) to make them available to you.

## Serializing your model

When you are ready to convert your model or application into a format that can be easily distributed and reconstructed by others, use Anaconda Enterprise to [deploy it](./deploy-model).

* YAML: supports non-hierarchical data structures & scalar data
* JSON: for client-server communication in web apps
* HD5: designed to store large amounts of hierarchical data; works well for time series data (stored in arrays)

<Note>
  Your model or app must be written in a programming language that supports object serialization, such as Python, PHP, R or Java.
</Note>