Integrating AI - Soft20/Business-Intelligence GitHub Wiki

Assignment 3

Objectives

Upgrade your business data story by implementing AI analysis in it.

• Select relevant ML methods and development tools.
• Create the AI module.
• Integrate it with the other modules in your data story, as appropriate, in a new AI prototype of your product.
• Export your solution files to your git repository.

Selected Machine Learning methods and Development Tools

For this assignment we wanted to use the data we found to create a model that could predict if a person have a probability of developing stress. We chose to use a Linear Regression model from scikit-learn for creating our trained model. The implementation of this can be found in the notebook below.

Creating ML model - notebook

After creating the model we wanted to implement it with Tableau via TabPy, however we faced a lot of challenges with the integration in Tableau. Instead we ended up making a Flask Server with interactive templates which we later implemented in Tableau as a webview. This can be found via the link below along with a short guide of how to run it.

Integrating ML model

The final result of the webview in Tableau looks accordingly