UNIT 016 h allocated
Boosting mechanics
- Residual fitting
- trees
- learning rate
- regularisation
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MACHINE LEARNING / SPECIALIST
ML220Ensembles, XGBoost & interpretable decisions
24 h productive allocation9 h 36 m learning + 14 h 24 m training4 units · 1 assessed practical brief
Detailed course plan and training brief. A complete taught course pack is in preparation. The linked foundation module, where shown, is a smaller available resource.
BEFORE YOU BEGIN
A clear starting point.
Prerequisites: ML201
Specialist studio; environment and faculty must be confirmed before scheduling
WHAT YOU SHOULD BE ABLE TO DEMONSTRATE
- Explain the assumptions and failure modes in boosting mechanics.
- Complete the practical: benchmark a boosted model against a simpler baseline using equal tuning budgets.
- Defend the resulting search ledger with reproducible evidence.
THE SUBJECTS / FOUR CONNECTED UNITS
What you will study.
UNIT 026 h allocated
Controlled tuning
- Validation design
- search budget
- early stopping
- reproducibility
UNIT 036 h allocated
Interpretability
- Feature attribution
- dependence plots
- correlated inputs
- local versus global explanations
UNIT 046 h allocated
Decision design
- Thresholds
- calibration
- slice errors
- operational costs
THE TRAINING STUDIO
Make the subject
visible in your work.
Benchmark a boosted model against a simpler baseline using equal tuning budgets.
Evidence to produce
- Search ledger
- baseline comparison
- error slices
Training brief for supervised delivery. Code, datasets, answer keys and environment acceptance must be completed in the full course pack before delivery is confirmed.
ASSESS THE REASONING
A question you
should be able to answer.
Why is feature importance not a causal explanation?
Review dimensions
Technical correctness · reproducibility · interpretation of results · failure analysis · individual explanation. Course-level rubric and faculty moderation form part of the final adopted teaching pack.
External reference access, hardware, cloud accounts and paid services are separate. No third-party certification is included by implication.