Job category:Artificial Intelligence

Choosing Inputs and Reading Results Responsibly

Learn to distinguish between predicting recorded outcomes and grouping unfamiliar patterns. You’ll practice assessing if data reflects your real-world cases and treating evaluation as a business decision. Master the "Fresh-Case Check" and the "Two-Mistake Trade-off" to weigh missed cases against false alarms, ensuring AI performance aligns with your operational tolerance for risk.
4 lessons
12 practices
1 hour
Badge for Feature Engineering,
Feature Engineering

Course details

Choosing Defensible Inputs
Understanding Inputs in Everyday Work
Screening a Proposed Input List
Trimming the Input List

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