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Machine Learning Foundations / Module 7

Module 7 check

Module 07 Assessment: Pipeline Reproducibility Check

Assessment ID: ML-M07-QA01 Estimated active time: 35-50 minutes Status: Draft

Part A: Concept checks

Answer in one or two sentences.

  1. At what point in your pipeline is the split performed, and why there?
  2. Which statistics are computed from training data only?
  3. What score do you get if the scaler is fitted on the whole dataset instead?
  4. Which of those two numbers is honest, and why?
  5. What does your pipeline do with a category it has never seen?

Part B: Applied task

Use the supplied synthetic dataset to complete the module activity: Build a pipeline with imputation, scaling, one-hot encoding, and a model.

Part C: Explanation

Explain the leak you demonstrated, why it inflates the score, and what the pipeline still does not handle.

Rubric

LevelEvidence
PassCompletes the activity, explains the output in plain English, compares or limits the result properly, and avoids overclaiming.
ReviseCompletes most of the task but misses one important comparison, limitation, or data-safety boundary.
Not yetTreats synthetic results as real-world proof, omits the required evidence, or ignores the module safety rule.

Safety rule

Do not use real personal, confidential, employer, client, health, financial, authentication, or sensitive data.