AI-Driven Dairy Health: Predicting Milk Yield & MastitisAI-Driven Dairy Health: Predicting Milk Yield & Mastitis
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This project features a machine learning pipeline that utilizes a Random Forest Classifier to predict milk yield fluctuations and detect subclinical mastitis in dairy cattle. By integrating multi-parameter data including Somatic Cell Count (SCC), electrical conductivity, and lactation stages,the model identifies early-stage health deviations that often bypass manual inspection. This proactive approach enables precision livestock management, allowing for targeted veterinary intervention to minimize production losses and improve overall animal welfare.
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