Food Delivery Time Prediction Model

• Tech Stack: Python, Scikit-learn, Pandas, NumPy, Matplotlib
• Project Focus: Predicting delivery time for food orders using machine learning
• GitHub Repository: Project Link

This project involves building a machine learning model to predict food delivery times for restaurants. It follows a modular structure to ensure scalability and reusability:

• Data Pipeline: Organized data storage with directories for raw, interim, processed, and external data.
• Model Development: Scripts for data preprocessing, feature engineering, model training, and predictions are housed in the src directory.
• Documentation and Reporting: Comprehensive documentation in Sphinx format and analysis reports with visualizations in reports.
• Version Control: Makefile for streamlined execution of data preparation and model training tasks.
• Reproducibility: Detailed requirements.txt for replicating the analysis environment.

The model utilizes features like order distance, time of day, and restaurant-specific metrics to deliver accurate delivery time predictions, aiding in improving customer satisfaction and restaurant efficiency.