Built an AI tool that cleans datasets, fills missing values, and predicts unknown fields [P]

I built a Streamlit-based AI data analysis tool that:

• Fills missing values using ML models (not just mean/median)

• Predicts any missing column using n-1 inputs

• Detects anomalies

• Shows correlations and feature importance

• Lets you download the updated dataset (Attached images show the UI and before vs after CSV file with a sample CSV available on the GitHub page, as well as an image showing the achieved performance metrics)

I wanted to test how well it works on real-world incomplete datasets.

Would love feedback on:

- model approach

- accuracy issues

- any improvements I should make

GitHub: https://github.com/WALKER00058/ML-data-analysis/tree/main