Automated Topic Modeling Workflows Done Right

In our previous blog posts of this series, we have introduced Topic Models, BigML's latest resource that helps you find thematically related terms in your unstructured text data, explained how to use it through the BigML Dashboard and the API, and lastly showed how to apply Topic Models in a real-life use case. This post will focus on automating LDA workflows by using WhizzML, a DSL for Machine Learning that provides programmatic support for all the resources you work with in our platform. Let's dive in by creating a Topic Model and making a prediction with it. In BigML, you can perform single instance predictions (referred to as a Topic Distribution) or in batch mode, which is called Batch Topic Distribution. Firstly, we will create a Topic Model without specifying any particular configuration option, that is, relying on default settings.