README.md

metadata

title: Credit Worthiness Risk Classification
emoji: 📈
colorFrom: blue
colorTo: indigo
sdk: gradio
sdk_version: 6.14.0
python_version: '3.10'
app_file: app.py
pinned: false

Credit Worthiness Risk Classification

End-to-end classification case study for credit risk prediction, including preprocessing, model selection, and app delivery.

Objective

Build and evaluate models to classify credit applicants by risk profile in a reproducible workflow.

What Is Included

• data preparation and feature engineering steps;
• supervised models: Logistic Regression, Decision Tree, Random Forest;
• hyperparameter tuning with GridSearchCV;
• model evaluation pipeline;
• lightweight Gradio app for interactive inference (app.py).

Dataset

• Local path: data/raw/german_credit.csv
• Source: Kaggle - German Credit Dataset

Run Locally

pip install -r requirements.txt
python app.py

Project Metadata

• sdk: gradio
• sdk_version: 6.14.0
• app_file: app.py
• license: Apache-2.0