When creating a machine learning model with Python, a common question is how to make the solution available for consumption from client apps or even for testing.

The objective of this session is to explain how a portable and consumable machine learning solution can be integrated within external applications.

This session is 100% practical and we will use the following technologies:

* Python (and various libraries) to create a classification Machine Learning model
* SQLite or SQL Server as data repository
* ASP .NET Core for the API the apps will connect to in order to consume the ML model
* Docker to create a container that includes the entire solution
* (If time allows it) A mobile application in Xamarin to interact with the implemented ML solution