Documentation
README
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
This is the opening of the README. Read the full README on GitHub.