Gen AI Lingo

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What does better actually mean?

Criteria, precision, recall, thresholds, subgroups and sample size.

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What you’ll learn

  1. Start with a useful success criterion

    Choose a metric that matches the actual task.

    About 4 minutes · Open activity

  2. Accuracy can hide rare failures

    Recognize an unhelpful high accuracy score on imbalanced examples.

    About 4 minutes · Open activity

  3. Precision asks about the flagged cases

    Interpret precision from a supplied visual count.

    About 4 minutes · Open activity

  4. Recall asks about all relevant cases

    Interpret recall from a supplied visual count.

    About 4 minutes · Open activity

  5. Changing a threshold changes the errors

    Explain a false-alarm versus missed-case tradeoff.

    About 4 minutes · Open activity

  6. Test the people and situations that matter

    Identify a group or condition hidden by an average.

    About 4 minutes · Open activity

  7. A benchmark is a sample of tasks

    Identify what a published score leaves outside its scope.

    About 4 minutes · Open activity

  8. Small differences need enough evidence

    Recognize uncertainty in a tiny comparison.

    About 4 minutes · Open activity

  9. Read a scorecard carefully

    Inspect a fictional classifier's flags, missed cases and subgroup results, and explain why the headline score is insufficient.

    About 5 minutes · Open activity