📊 Classifier Models — Supervised Machine Learning

This section contains comprehensive resources for understanding, evaluating, and optimizing classifier models.

It includes both statistical and visual interpretation guides, detailed EDA strategies, and in-depth modeling guidebooks to support end-to-end classifier workflows.

📂 Available Resources

📊 Interpretation Guides

• 📊 Advanced Classifier Visual Interpretation Guide — Techniques for deep-dive visual analysis of classifier performance.
• 📊 Classifier Statistical Summary Sheet — Quick-reference sheet for key classifier evaluation metrics.
• 📊 Visual Interpretation Guide for Classifier Models — Step-by-step visual analysis methods for classification results.

📘 Guidebooks

• 📘 Advanced Classifier Modeling Guidebook — In-depth methods for advanced classification modeling and tuning.
• 📘 EDA Guidebook for Classifier Models — Exploratory data analysis practices tailored to classifiers.
• 📘 Machine Learning & Classifier Models Guidebook — Comprehensive reference for integrating classifier models into ML pipelines.