Training models#

Data Science & AI Workbench 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 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 Workbench to deploy it.

  • 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)


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