My journey through the ML Zoomcamp - Cohort 2025

 Module 4: Evaluation Metrics for Classification This module was about how to properly evaluate classification models and handle imbalanced datasets.  The following were covered Accuracy, precision, recall, F1-score ROC curves and AUC Cross-validation Confusion matrices Class imbalance handling

Module 3: Machine Learning for Classification In this module we create a customer churn prediction system using logistic regression and learn about feature selection.   Topics covered included: Logistic regression Feature importance and selection Categorical variable encoding Model interpretation