The ML-system option — six boring stages that get a repo taken seriously (step 7/7) · capstone

Checkpoint

One last thing before we move on. Same surface as a write step — but the lesson doesn't complete until this passes.

Last exercise of the capstone. Three candidate systems sit in your portfolio folder; decide which one goes in the README. Write readiness_report(system) returning a dict with:

stages_present: how many of the six REQUIRED stages appear in system["stages"]
gate: "ship" if eval_accuracy >= gate_threshold, else "hold"
portfolio_ready: True only when all six stages are present AND the gate says "ship"

The runner prints one line per system. Note what it punishes: price-model has the best accuracy of the three and still fails — no monitoring hook, no portfolio. Expected output:

churn-predictor: 6/6 stages, gate ship, ready: True
price-model: 5/6 stages, gate ship, ready: False
spam-filter: 6/6 stages, gate hold, ready: False

Checkpoint

One last thing before we move on. Same surface as a write step — but the lesson doesn't complete until this passes.

Last exercise of the capstone. Three candidate systems sit in your portfolio folder; decide which one goes in the README. Write readiness_report(system) returning a dict with:

stages_present: how many of the six REQUIRED stages appear in system["stages"]
gate: "ship" if eval_accuracy >= gate_threshold, else "hold"
portfolio_ready: True only when all six stages are present AND the gate says "ship"

The runner prints one line per system. Note what it punishes: price-model has the best accuracy of the three and still fails — no monitoring hook, no portfolio. Expected output:

churn-predictor: 6/6 stages, gate ship, ready: True
price-model: 5/6 stages, gate ship, ready: False
spam-filter: 6/6 stages, gate hold, ready: False

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The ML-system option — six boring stages that get a repo taken seriously — step 7 of 7