Continuous delivery for data science models

Tired of wrapping pickled models in server logic? me too! The biggest bottleneck in delivering machine learning services is the handover from data science to engineering.

Providing scientists with a predicable and safe way to deploy their own models will decouple the engineering and data science efforts allowing each departments to focus on delivering value instead of completing repetitive tasks.

This was achieved by exposing a pub/sub interface where data models just have to register as services and they are automatically exposed to the rest of the organisation.

Comments

Comments are closed.