{"id":26015865,"url":"https://github.com/codeofrahul/food-delivery-time-prediction-mlops","last_synced_at":"2025-09-10T14:09:14.367Z","repository":{"id":258802679,"uuid":"875284553","full_name":"CodeofRahul/Food-Delivery-Time-Prediction-MLOPS","owner":"CodeofRahul","description":"In today's fast-paced world, efficient food delivery is crucial. This project presents a robust and modular end-to-end machine learning pipeline designed to predict food delivery times. 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This project presents a robust and modular end-to-end machine learning pipeline designed to **accurately predict food delivery times**. By leveraging a rich dataset containing delivery personnel details, restaurant locations, order information, and environmental factors like weather and traffic, I've developed a model capable of providing valuable insights for optimizing delivery operations.\n\nThis project emphasizes clean, maintainable, and reproducible code, showcasing best practices in modern machine learning engineering. It's built to handle real-world challenges, offering a scalable and adaptable solution for predicting delivery times.\n\n## Key Features\n\n* **Accurate Delivery Time Prediction:** Utilizes a comprehensive dataset to build a predictive model for food delivery times.\n* **Modular Architecture:** The pipeline is designed with a clear separation of concerns, facilitating easy understanding, modification, and extension.\n    * **Components:** Independent modules for data ingestion, transformation, model training, and evaluation.\n    * **Pipelines:** Orchestrated end-to-end workflows for training and prediction.\n* **Batch Prediction:** Implements a batch prediction system for processing multiple orders efficiently.\n* **Robust Error Handling:** Custom exception handling and logging ensure stability and maintainability.\n* **Data Validation:** Utilizes schema validation to maintain data integrity.\n* **Reproducibility:** `requirements.txt` and `setup.py` ensure consistent environments.\n\n* **`Artifact`:** Stores trained models and other artifacts.\n* **`Data`:** Contains data ingestion related files.\n* **`Prediction`:** Handles batch prediction outputs.\n* **`config`:** Stores configuration templates.\n* **`src`:** Contains the core application code.\n    * **`components`:** Individual modules for different pipeline stages.\n    * **`config`:** Configuration-related code.\n    * **`constants`:** Project constants.\n    * **`entity`:** Data entity definitions.\n    * **`exception`:** Custom exception handling.\n    * **`logger`:** Logging utilities.\n    * **`pipeline`:** End-to-end pipeline logic.\n    * **`utils`:** Utility functions.\n    * **`__init__.py`:** Makes directories Python packages.\n* **`templates`:** HTML templates for web app.\n* **`app.py`:** Main application file.\n* **`exception.py`:** Custom exception definitions.\n* **`logs.py`:** Logging configuration.\n* **`main.py`:** Main execution script.\n* **`pipeline.txt`:** Pipeline execution details.\n* **`requirement.txt`:** Project dependencies.\n* **`schema.yaml`:** Data schema definition.\n* **`setup.py`:** Project setup and packaging.\n\n## Getting Started\n\n1.  **Clone the repository:**\n\n    ```bash\n    git clone https://github.com/CodeofRahul/Food-Delivery-Time-Prediction-MLOPS.git\n    cd Food_Delivery_Time_Prediction-MLOPS\n    ```\n\n2.  **Create a virtual environment:**\n\n    ```bash\n    conda create -p env python=3.9 -y\n    conda activate env/ --\u003e CMD \u003cbr\u003e\n    source activate env/ --\u003e git bash\n    ```\n\n3.  **Install dependencies:**\n\n    ```bash\n    pip install -r requirements.txt\n    ```\n\n4.  **Run the application:**\n\n    ```bash\n    python app.py\n    ```\n\n5.  **Run the training pipeline:**\n\n    ```bash\n    python main.py\n    ```\n\n## Usage\n\nThis project can be used as a foundation for building and deploying food delivery time prediction systems. Its modular design allows for easy customization and extension.\n\n## Contributing\n\nContributions are welcome! Please submit pull requests or open issues to contribute.\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcodeofrahul%2Ffood-delivery-time-prediction-mlops","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcodeofrahul%2Ffood-delivery-time-prediction-mlops","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcodeofrahul%2Ffood-delivery-time-prediction-mlops/lists"}