In my last post I surveyed the growing array of options for deploying your ML models into production. In this post, we’ll create a demo to see how simple it is to develop your own service using Python’s Flask library.
There are a number of cases where you might not be able to use a cloud service to host your model and would be required to roll-your-own inference service. In many large enterprises, on-premise solutions are mandatory. Approvals to purchase third-party solutions can also be lengthy and complex. So developing your own small service may be the best solution.