ML Experiment Evaluation
Plan evaluation strategies for machine-learning product changes. Use when deciding between offline evaluation, interleaving, online A/B tests, multi-armed bandits, or model filtering for ranking, recommendation, search, personalization, or other ML-powered user experiences.
Product Managementv0.1.0MITpractical-ab-testingnext-level-ab-testingab-testingexperimentationmachine-learning
Install
npx skills add LVTD-LLC/skills --skill ml-experiment-evaluationFrom `SKILL.md`
Use this skill to choose how to evaluate machine-learning product changes before they consume live experiment traffic or affect users. It focuses on offline evaluation, offline-online correlation, interleaving, model filtering, and when classic A/B testing or