This article explains how Flask helps bridge the gap between machine learning models and real-world applications by exposing models as REST APIs. It covers the complete implementation workflow also.
Because our last article in the 'ML in production' series used Flask with Docker, we are continuing with Flask here. This approach allows us to delve deeper into the framework."
Why not fastapi ? There is async benefit aswell
Sam,
Because our last article in the 'ML in production' series used Flask with Docker, we are continuing with Flask here. This approach allows us to delve deeper into the framework."
You can use Flask API as well.