Upload 2 files

README.md

@@ -0,0 +1,32 @@
+---
+title: Credit Card Fraud Detection with DuckDB
+emoji: 💳
+colorFrom: blue
+colorTo: purple
+sdk: gradio
+sdk_version: "4.44.0"
+python_version: "3.10"
+app_file: app.py
+pinned: false
+---
+
+# Credit Card Fraud Detection with DuckDB and Medallion Architecture
+
+This project demonstrates an end-to-end pipeline for credit card fraud detection. It uses DuckDB to process data in a Medallion Architecture (Bronze, Silver, Gold) and trains a Random Forest model to identify fraudulent transactions.
+
+## Project Structure
+
+- `data/`: Contains the raw CSV datasets (`fraudTrain.csv`, `fraudTest.csv`).
+- `src/`: Contains the Python scripts for the data pipeline and model training.
+  - `bronze.py`: Ingests raw data into the bronze layer.
+  - `silver.py`: Cleans and transforms data for the silver layer.
+  - `gold.py`: Creates aggregated features for the gold (analytics) layer.
+  - `train.py`: Trains a `RandomForestClassifier` on the gold data and saves the model.
+- `models/`: Directory where the trained model is saved.
+- `requirements.txt`: Lists the required Python packages.
+
+## How to Run
+
+1. **Install dependencies:**
+```bash
+pip install -r requirements.txt

app.py

@@ -0,0 +1,6 @@
+import gradio as gr
+
+def status():
+    return "Credit Card Fraud Detection Pipeline is ready. Run training using src/train.py"
+
+gr.Interface(fn=status, inputs=[], outputs="text").launch()