📦 Delivery Time Prediction App

This is a Streamlit-based web application that predicts delivery time for an order based on multiple input features like shipping method, customer location, weather, distance, and more. The prediction model is trained using Python's scikit-learn library and serialized using pickle.

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🚀 Features

• Predicts delivery time in days.
• Uses a trained machine learning model stored in a .pkl file.
• Clean and user-friendly UI built with Streamlit.
• Input features include: Product Category, Customer Location, Shipping Method, Shipping Priority, Weather Condition, Package Weight, Package Size, Distance, Warehouse Availability, Delivery Type
• Output feature: Delivery Time

🧠 Model Training

The model is trained using the following pipeline:

• Data preprocessing using pandas and sklearn
• Feature scaling using StandardScaler
• Model: LinearRegression
• Evaluation metrics: MAE, R²
• Trained model is saved as delivery_time_n_model.pkl

📦 Installation

Clone the repository

git clone https://github.com/darshan1654/Delivery-Time-Prediction-App.git
cd Delivery-Time-Prediction-App

pip install -r requirements.txt

streamlit run App.py

📝 License

This project is licensed under the MIT License.