Getting Started¶
Prerequisites¶
- Python 3.11+
uvinstalled- Git
5-Minute Setup¶
Pick Your First Project¶
- Easiest start:
projects/sota-supervised-learning-showcase - Causal decisioning:
projects/causalml-kaggle-showcase - Modern unlabeled-data workflows:
projects/sota-unsupervised-semisup-showcase - Production monitoring and serving:
projects/mlops-drift-production-showcase - Credit-risk capstone from course notebooks:
projects/credit-risk-classification-capstone-showcase - Responsible AI auditing:
projects/xai-fairness-audit-showcase - Rollout and rollback simulation:
projects/model-release-rollout-showcase - Data diagnostics and leakage checks:
projects/eda-leakage-profiling-showcase - Ranking model training fundamentals:
projects/learning-to-rank-foundations-showcase - Ranking API serving and contracts:
projects/ranking-api-productization-showcase - Time-aware demand forecasting foundations:
projects/nyc-demand-forecasting-foundations-showcase - Demand API with metrics and tracing hooks:
projects/demand-api-observability-showcase
First Run Pattern¶
Then run the recommended quickstart in that project's README.
Recommended Root Checks¶
After your first project run, validate the repository-level workflow:
make check-contractsregenerates missing supervised artifacts in quick mode and validates contract files.make checkruns lint, type checks, tests, and contract verification across projects.make verifyvalidates per-project artifact manifests where available.make docs-checkruns a strict MkDocs Material build for docs consistency.
Docs Site¶
Run local docs with:
Build static docs output with:
Topic Coverage Guide¶
For a direct mapping from course topics to projects, commands, and artifacts, use:
docs/aspect-coverage-matrix.md