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Project phase 1
Plan the work
State the goal, audience or user, and the evidence a strong result needs. Explain how Classification changes your plan.
Machine Learning with Python · Lesson 4 project
Design a threshold-and-harm analysis
A threshold choice tied to false-positive and false-negative costs, plus metrics that reveal the tradeoff.
Lesson project · Classification decision
Design a threshold-and-harm analysis
A threshold choice tied to false-positive and false-negative costs, plus metrics that reveal the tradeoff.
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Project phase 2
Create the deliverable
For a safety classification, list the cost of a false positive and false negative. Choose a probability threshold and explain why accuracy alone may hide the most harmful errors.
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Project phase 3
Prove and improve
Use Probability threshold and False negative to check the result. Record one piece of evidence, one correction, and one improvement you would make next.
Close the loop
Explain what changed.
After the checks pass, name one decision, one failure you corrected, and one improvement you would make next. That explanation is part of the project.