ModelTraining

Training a model from data — feature selection, train/val/test splits, evaluation metrics.

Why we need this / what value this brings

A model is only as good as its evaluation — training without a rigorous eval setup produces false confidence.

When to use this

Once there's labeled data and a clearly defined prediction target.

How to use or implement this

Hold out a proper validation/test split before touching the test set, and pick an evaluation metric that reflects the actual business cost of errors.

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Empty folder — drop notes, links, and findings here as you research.