Overview This project focuses on crop health management and monitoring using machine learning techniques. The goal is to provide farmers and agricultural professionals with tools to monitor the health of crops, predict potential issues, and suggest appropriate actions to maintain optimal crop health.

Features Data Collection: Integration with sensors and satellite data for real-time monitoring. Preprocessing: Data cleaning, normalization, and augmentation. Model Training: Various machine learning models for disease detection, yield prediction, and more. Visualization: Interactive dashboards and visual representations of crop health. Alert System: Automated alerts for potential issues and recommendations.

Contributing Contributions are welcome! Please submit a pull request or open an issue to discuss any changes.

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

Acknowledgments Thanks to the open-source community for providing tools and libraries that made this project possible. Special thanks to the agricultural experts and farmers who provided valuable insights and feedback.