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Retail_sales_prediction
Pavithra64/Retail_sales_prediction
Retail_sales_prediction is a machine learning model from Pavithra64. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This Streamlit app predicts daily retail store sales using a trained Random Forest regression model.
Access
Public
Updated Jan 28, 2026
Repo size
1.8 GB
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0
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Repo makeup
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.pkl1.8 GB · 100%
At a glance
- Access
- Public
- Created
- Jan 26, 2026
- Updated
- Jan 28, 2026
- SHA
- de733889
Model card
From the Hugging Face model README
🛒 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
- User inputs store and date-related features
- App downloads the trained model if not available
- Model predicts expected sales
- 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
- Created
- Jan 26, 2026
- Updated
- Jan 28, 2026