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Free preview: Orchestrating training — MLOps: Machine Learning in Production

Free preview lesson · MLOps: Machine Learning in Production · Module 1: ML pipelines

Orchestrating training

A model that cannot be reproduced cannot be trusted. Experiment tracking records what produced each result.

What to record

Code version, data version, parameters, metrics and the resulting artefact.

Why it matters

When performance drops you can compare against a known good run.

Start small

Even a shared spreadsheet beats nothing; then move to a tracking tool.

Common pitfall

Overwriting model files without recording what changed.

Action step

List what you would need to rebuild your last model exactly.

This is one lesson from MLOps: Machine Learning in Production.

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