An ever-increasing number of organisations are developing applications that involve machine learning (ML) components. The complexity and diversity of these applications calls for engineering techniques to ensure they are built in a robust and future-proof manner.

On this website we collect, validate and share engineering best practices for software including ML components. To this end, we study the scientific and popular literature and engage with machine learning practitioners.

For more information access our catalogue of ML engineering best practices or read our annual report on the State of Engineering Practices for Machine Learning.