Splitting data into Training and Test data sets is part of what?

Splitting data into training and test data sets is an important step in the machine learning data

preparation process. This process involves splitting the data into subsets, usually in a 70:30 ratio, to

create a training set and a test set. The training set is used to train the machine learning model, while

the test set is used to evaluate the model’s performance. This process allows for the model to be

tested and evaluated on data that it has not seen before, in order to ensure that it is accurate and

able to generalize to new data.

BCS Foundation Certificate In Artificial Intelligence Study

Guide, https://bcs.org/certifications/foundation-certificates/artificial-intelligence/