Find Friends App
Data of creation: 2024-10-09
Project description
The aim of the project was to create an application that would enable the use of a clustering model to match a user to the appropriate group from a loaded data set (data comes from an anonymized survey) - based on data provided by the user.
Main functionalities
- The user filters basic data, such as: age, education, gender, favorite animals, or favorite places - corresponding to their preferences
- Then the previously trained clustering model creates the appropriate number of clusters for the survey data and matches the user's preferences to the matching group
- Finally, using LLM, adequate cluster descriptions are generated
ML model training
I used Scikit-learn tools and I have included the implementation in a notebook ready for download:
Download Notebook: Model training
Download Notebook: Model training
Clusters naming
I used the LLM model and I have included the implementation in a notebook ready for dowlonad:
Download Notebook: Clusters naming
Download Notebook: Clusters naming
Skills
- Python
- Langfuse
- OpenAI
- Streamlit
- Scikit-learn
- Plotly
- PyCaret (Clustering)
- NumPy
- Matplotlib
Sample photos
Application testing
The application has been deployed on the Streamlit Community App and is available for public use.