ML Pipeline

Purpose

Build a machine learning pipeline that produces the same model twice and behaves in production the way it did in training. The two defining failure modes are irreproducible training and train/serve skew — the model sees different features in production than it saw in training, and quietly degrades.

When to Use

• Building a training or inference pipeline.
• A model that performed well offline and poorly in production.
• Setting up monitoring for a deployed model.
• Establishing a retraining cadence.

Capabilities