PROFESSIONAL • Responsible AI and Security

Evaluation Playbook for retail demand forecasting #19

This lesson focuses on strengthen experiment tracking using a practical retail demand forecasting scenario. You will apply commands: docker build -t ai-service . | kubectl apply -f deployment.yaml | prometheus + grafana dashboards. The code example demonstrates a concrete workflow aligned with this lesson objective, not generic filler.

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If this never completes: start PostgreSQL, check DATABASE_URL and DIRECT_URL in .env, run npx prisma db push. Optional: set SKIP_RUNTIME_CATALOG_SEED=1 to skip heavy catalog seed while debugging.