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Example Machine Learning Workflow

A Machine Learning workflow may consist of the following multiple steps, performed in a sequential order through the units specific to Machine Learning which are described in this page.

Training a Model

As below:

  1. Selecting target properties for prediction
  2. Generating and gathering the training data set
  3. Cleaning the data to prepare it for training
  4. Transforming the data through scaling, etc.
  5. Selecting the best features to base the model upon
  6. Training the Machine Learning model

Making Predictions

As below

  1. Train model as explained in the previous section
  2. Predicting new properties from the trained model


The user is referred to the tutorial section on machine learning for more detailed information on the above steps.