Using the Vital AI software to make predictions

In this series of blog posts, I’ll introduce components of the Vital AI software used to make predictions via machine learning models.

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We’ll use the venerable “20 Newsgroup” dataset often used in text classification, which consists of around 20,000 text articles across 20 categories.  The dataset is available here: https://github.com/vital-ai/vital-datasets/tree/master/20news

The primary steps are:

  • Set up a data model
  • Create the data set
  • Define the prediction model
  • Run the machine learning training
  • Evaluate the trained model
  • Use the model to make ongoing predictions

In this example, our predictions will be the categories assigned to the text – such as a category like “baseball” if the text is about baseball.

Next: Introduction to Big Data Models

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