This web app uses machine learning to generate recommendations (association rule learning) from an input CSV.
The input CSV needs the following input columns:
- Unique transaction ID (like an invoice number)
- Item name
To see what the output looks like, click 'Get rules' and rules will be generated using built in sample data.
Sample data used is a variation of: Online Retail Data Set
Clone this repository into a new environment, install dependencies from requirements.txt
and enter the following in your terminal:
streamlit run ruler.py
This will create a local web server which should open in your default browser. If not, just use one of the links returned in your terminal.
- Web app built with Streamlit.
- Associaton rules generated using Pycaret's Association Rules module.