Continuous integration (CI) is the practice of automatically testing and integrating code changes into a shared repository.
In a machine learning project, CI can be very useful for several reasons:
- Catching errors early: CI facilitates the early identification of errors by automatically testing any code changes made.
- Faster feedback and decision-making: By providing clear metrics and parameters, CI enables faster decision-making, freeing up reviewer time for more critical tasks.
In my latest article and video, you will learn how to create CI in an ML project.
