CI/CD for ML: Building Reliable Deployment Pipelines
Principles that separate robust ML CI/CD from fragile scripts Build → Test → Evaluate → Deploy: exact responsibilities for each stage Canary deployments and automated rollback: minimizing blast radius Model and data testing taxonomy you can operationalize today Tooling patterns and CI/CD examples f…
Read the full story at DEV Community — Machine Learning ↗
Timeline · 1 report
- 2026-11-07 14:14 · DEV Community — Machine Learning
CI/CD for ML: Building Reliable Deployment Pipelines