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.
To train the AI model I used Scikit-learn tools and I have included the implementation in a notebook ready for download:
Download Notebook: Model training
To generate Clusters names I used the LLM model and I have included the implementation in a notebook ready for dowlonad:
Download Notebook: Clusters naming
Skills:
- Python,
- Langfuse,
- OpenAI,
- Streamlit,
- Scikit-learn,
- Plotly,
- PyCaret (Clustering),
- NumPy,
- Matplotlib.
Sample photos:
The application has been deployed on the Streamlit Community App and is available for public use.
Link to repository: https://github.com/kasjansmigielski/find_friends_app
Link to app: https://find-friends-app.streamlit.app/