Machine Learning
- Modeling (What): the process of creating a model to understand how the collected data interact in an specified environment
- Trial and Error (How): the process of making guesses about what will happen, measuring the output, and updating the model accordingly
- Predictions (Why, Goal): making correct predictions with new data