hello·ai

Classifying with small models · Module D of 6

Knowing it works

How do I know it is right, and right for whom?

Precision, recall and the metrics built on them, slicing, honest data splits, small samples, and where labels come from.

Topics in this module

Topics

🔒 Unlocks at 1 of 1 topics in Module C — 0 done.
  1. D1

    Precision and recall Planned

    "Did we find them all?" versus "when we said it, were we right?"

  2. D2

    F1 and macro-F1 Planned

    The harmonic mean punishes imbalance; macro weights every class equally.

  3. D3

    Slicing Planned

    Report metrics per slice, because one number hides everything.

  4. D4

    Train, validation, test Planned

    Textbook, practice tests, final exam.

  5. D5

    Small samples Planned

    Many knobs on little data overfit; confidence intervals say how much.

  6. D6

    Where labels come from Planned

    Humans, LLMs and weak labels, and never grading a system with its own answers.