Overview of a standard Amazon Machine Learning workflow

The Amazon Machine Learning service is available at https://console.aws.amazon.com/machinelearning/. The Amazon ML workflow closely follows a standard Data Science workflow with steps: 

1. Extract the data and clean it up. Make it available to the algorithm.
2. Split the data into a training and validation set, typically a 70/30 split with equal distribution of the predictors in each part.
3. Select the best model by training several models on the training dataset and comparing their performances on the validation dataset.
4. Use the best model for predictions on new data.

As shown in the following Amazon ML menu, the service is built around four objects:

• Datasource
• ML model
• Evaluation
• Prediction

The Datasource and Model can also be configured and set up in the same flow by creating a new Datasource and ML model. Let us take a closer...