MLOps Assignment 2

Installation
Install Apache Airflow:


Install Dependencies:

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pip install -r requirements.txt
Usage
Start the Airflow Web Server:

css
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airflow webserver --port 8081
Start the Airflow Scheduler:

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airflow scheduler
Access the Airflow Web Interface:

Open a web browser and go to http://localhost:8081.
You can trigger DAG runs and monitor their execution from the Airflow web interface.
Directory Structure
graphql
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mlops-airflow/
├── dags/
│   └── mlops_dag.py          # Apache Airflow DAG script
├── scripts/
│   └── scrapeLinks.py        # Python script for data extraction
└──── processed_data.csv    # Processed data stored on Google Drive
Contributing

License
This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgements
Thanks to Apache Airflow for providing a powerful platform for workflow automation.
Special thanks to DVC for enabling efficient data version control.