Model Evaluation

Overview

This skill focuses on comprehensive evaluation of machine learning models across the entire ML lifecycle. It covers metric selection, validation strategies, fairness assessment, training debugging, hyperparameter tuning, LLM evaluation, A/B testing, and production monitoring for ensuring model quality and reliability.

When to Use This Skill

Use this skill when you need to: