# ML Model Evaluation

Skill · Data Science, Analytics and AI/ML

Canonical page: https://career.thegoodapps.co/skills/ml-model-evaluation

ML model evaluation is the practice of measuring how well a trained machine learning model performs on unseen data, using metrics like accuracy, precision, recall, F1 score, or AUC depending on the task. Data scientists rely on techniques such as train/test splits, cross-validation, and holdout sets to detect overfitting and compare candidate models before deployment. It is a core step in the ML lifecycle that determines whether a model is ready for production use.

Related skills: [Hyperparameter Tuning](https://career.thegoodapps.co/skills/hyperparameter-tuning)

## Open roles requiring ML Model Evaluation (0)

None of the roles we have read name this skill yet. A large share of the visible corpus has not been parsed for skills, so this is at least as likely to be our backlog as the market's verdict.