Modelling & Evaluation

Type of course:

Digital learning, Lesson

Language:

Duration:

10 minutes

Workload:

2 hours

Proficiency:

Beginner

Target:

Professionals

This nugget comprises one of the more fascinating stages of a machine learning project, and we will base our approach on the “Modelling” and “Evaluation” stages in the CRISP-DM methodology.

Formative assessment is presented in the end to support the student’s comprehension of the materials.

Learning outcomes

The student will describe the role of "Modelling" and "Evaluation" stages in the CRISP-DM methodology.
The student will recognize the importance of data splitting and randomization during the Modelling stage to ensure proper model training and its evaluation.
The student will identify the key considerations and metrics used in the Model Evaluation stage, including choosing appropriate performance metrics based on the problem's nature and priorities.