CD4ML: Automating ML from Data to Deployment
CD4ML extends CI/CD to manage ML's three axes of change: code, data, and models. It automates the entire lifecycle, enabling reliable updates for systems like sales forecasting.
Continuous Delivery for Machine Learning (CD4ML) applies CI/CD principles to automate the entire ML lifecycle, managing the three axes of change: code, data, and the model itself. It's essential for production systems like fraud detection that need frequent, reliable updates. The biggest footgun is treating ML as a research project by automating only the application code, leaving data prep, model training, and validation as slow, manual steps that accumulate massive technical debt.
Read the original → martinfowler.com
- #mlops
- #ci/cd
- #machine learning
- #deployment
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