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Crop Yield Prediction Using Machine Learning
- Accurate crop yield prediction is crucial for ensuring food security and optimizing agricultural practices.
- Traditional methods for predicting crop yields lack accuracy and scalability.
- Machine learning (ML) offers a more accurate and data-driven approach to crop yield prediction.
- ML models such as linear regression, random forests, SVMs, and CNNs have been successfully applied to crop yield prediction.
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