ML Zoomcamp Student Highlights Feature Selection Insights from Classification Module

A student has completed Module 3 of the ML Zoomcamp 2026, focusing on machine learning for classification. They noted that correlation analysis and mutual information scoring can yield different rankings for feature importance. In their exercise, a categorical feature was top-ranked by mutual information but invisible to standard correlation matrices. The student also emphasized verifying small performance differences in models before dismissing them as noise. Their next step in the course is Module 4, which covers evaluation metrics for classification.