What Did we Learn and What to Expect in Assignment 3

Module Learning Outcomes

By the end of the module, students are expected to:

• Split a dataset into train and test sets using train_test_split function.
• Explain the difference between train, validation, test, and “deployment” data.
• Identify the difference between training error, validation error, and test error.
• Explain cross-validation and use cross_val_score() and cross_validate() to calculate cross-validation error.
• Explain overfitting, underfitting, and the fundamental tradeoff.
• State the golden rule and identify the scenarios when it’s violated.

The assignment will concentrate on the learning objectives as well as building knowledge on existing concepts.

On to Assignment 3!