Deploy Machine Learning Models with Django

The simplest approach is to run the ML algorithm locally to compute predictions on prepared test data and share predictions with others. This approach is easy and fast in implementation. However, it has many drawbacks. It is hard to govern, monitor, scale and collaborate. The second, similar approach, is to hard-code the ML algorithm in the system's code.