In this project, you will learn how to create an AI enabled mobile app based on Tsetlin Machine (a new machine learning algorithm) using Kivy to forecast the number of Corona patients for the next day in different countries

More details about the machine learning algorithm (regression tsetlin machine) will be added soon. (https://github.com/cair/regression-tsetlin-machine)

• In order to obtain more accurate predictions, Corona incidences in the "data" folder should be updated and Regression Tsetlin Machine (RTM) should be retrained.

• At end of training, four .npy files will be generated for each country.

• Resulting .npy files, images in the "Image" folder, and "main.py" file should be placed in the same directory.

• At this stage, you can run the "main.py" file and see how the app works.

• In order to build the application, see the instructions on https://kivy.org/doc/stable/guide/packaging.html.

• Once the suppoting packages on https://kivy.org/doc/stable/guide/packaging-android.html are installed, create the buildozer by running "buildozer init" command.

• In the generated "buildozer.spec" file, add ".npy" and ".gif" extensions to the "source.include_exts" property.

• Now for an example, build the mobile application for Android by running "buildozer android debug deploy run" command.

The initial stage, asking you to select a country. Press on the "Country" button and select the country you want.

Once you select the country, the required input features will be displayed on the second half of the screen.

Enter the required features seperated by commas ("Next Feature" button) and press the "Predict" button at the end.

You can't predict without selecting a country.

You should add the right number of input features.