Features Detective App
Date of creation: 2024-10-30
Project description
The aim of the project was to create a universal application that allows for detecting the most important features in a given data set. In short - the user uploads data or loads a ready data set in the appropriate format, then selects automatic detection of the column they want to analyze or makes this selection themselves. Finally, they receive a generated graph of the significance of features that have the greatest impact on the previously selected column. The user also receives a clear description of the graph along with recommendations - what can be improved to, for example, improve the analyzed data.
Main functionalities
- The user can load a CSV/JSON file with data or use a ready-made sample dataset
- The user indicates the target column -> additionally, they can use automatic column detection (generated by LLM)
- The application automatically recognizes whether the loaded data is related to the regression or classification problem and selects the appropriate AI model training algorithm on this basis
- Based on the trained model, a chart containing the most important features is displayed
- Finally, the user receives a clear description of the chart along with recommendations - what actions to implement to improve the results related to the analyzed target data column
ML model training
I used PyCaret tools and I have included the implementation in a notebook ready for download:
Download Notebook: Model training
Download Notebook: Model training
Skills
- Python
- Langfuse
- OpenAI
- Streamlit
- PyCaret (Classification & Regression)
- Pandas
- Matplotlib
- Instructor
- Pydantic
- Boto3
Sample photos
