This project was realized for the FINTECH (055643) course, held at Politecnico di Milano, A.Y. 2021/2022.
Project supervisor: Raffaele Zenti.
Team members
- Teo Bucci (GitHub, Linkedin)
- Filippo Cipriani (GitHub, Linkedin)
- Gabriele Corbo (GitHub, Linkedin)
- Davide Fabroni (GitHub, Linkedin)
- Marco Lucchini (GitHub, Linkedin)
The aim of this project is to exploit machine learning techniques to create a cross-platform web-app to recommend products based on clients' need.
We have been provided with the dataset Needs.xls, which contains information about clients and products.
We followed a multi-tool approach, porting models to exploit each software's development strengths. We used MATLAB, R, for prototyping and Python with Streamlit module for deployment.
The prototyping part is in the dev folder while the Python part is in the models folder; finally the app.py file contains the Streamlit implementation.
The web-app is available here.
The presentation.pdf is in the output folder.