juniorAzure ML
What are Azure ML Pipelines?
Updated May 15, 2026
Short answer
Azure ML Pipelines automate end-to-end machine learning workflows.
Deep explanation
Azure ML Pipelines are workflows composed of reusable steps that automate machine learning operations such as data ingestion, feature engineering, training, evaluation, and deployment.
Pipelines improve reproducibility, modularity, and operational efficiency. They support parameterization, caching, scheduling, and CI/CD integration.
Real-world example
A logistics company schedules nightly retraining pipelines for delivery prediction models.
Common mistakes
- Hardcoding paths, building monolithic pipelines, and not reusing components.
Follow-up questions
- What is pipeline caching?
- Can pipelines run on schedules?
- Why are pipelines important?