Classical Machine Learning

Purpose: Build, evaluate, and debug tabular and unsupervised models correctly.

Outcomes

• Train regression and classification models.
• Avoid leakage and misleading metrics.
• Use ensembles.
• Cluster and reduce dimensions.

Audience

Engineers and analysts who want correct, debuggable tabular ML.