ML Engineering Principles

Guidelines for building reliable, reproducible machine learning systems.

When to Invoke

• Designing ML pipelines (training, serving)
• Feature engineering and data preparation
• Model evaluation and validation
• MLOps infrastructure decisions

ML Pipeline Design

Stages

Data Collection → Feature Engineering → Training → Evaluation → Deployment → Monitoring