Pavithra64/Retail_sales_prediction

🛒 Retail Sales Prediction

This Streamlit app predicts daily retail store sales using a trained Random Forest regression model.

🚀 Features

• Predict sales based on store and promotion details
• Clean interactive UI built with Streamlit
• Machine Learning model trained using Scikit-learn
• Model hosted externally to avoid GitHub size limits

🧠 Model Details

• Algorithm: Random Forest Regressor
• Trained on historical retail sales data
• Features include:
  • Day of week
  • Customers
  • Promotions
  • Holidays
  • Store type & assortment
  • Competition distance

🖥️ How it Works

1. User inputs store and date-related features
2. App downloads the trained model if not available
3. Model predicts expected sales
4. Prediction is displayed instantly

📦 Tech Stack

• Python
• Streamlit
• Pandas
• Scikit-learn
• Joblib
• Hugging Face Spaces

⚠️ Notes

• Model file is not stored directly in the repository
• The app downloads the model securely at runtime

👩‍💻 Author

Pavithra Palanivel

---

✨ Deployed using Hugging Face Spaces