Poultry Feed Consumption Predictor - Cobb 500 ML System
Félix Ruiz M.
Advanced Machine Learning system for predicting daily feed consumption in Cobb 500 chickens using Random Forest algorithm. Trained on real poultry farm data achieving 99%+ accuracy (R² > 0.99).
🔹 Industry Impact: Optimizes feed costs in commercial poultry operations 🔹 Exceptional Accuracy: R² > 0.99 with minimal prediction errors 🔹 Smart Features: 7 core variables + 4 engineered features 🔹 Production Ready: Complete training and prediction pipeline 🔹 Multi-Treatment Support: Handles different feeding treatments
Key Capabilities:
Predicts daily feed consumption by growth stage
Reduces feed waste and optimizes nutrition costs
Supports treatment comparison and optimization
Enables data-driven poultry farm management
Variables: Day, weight, weight gain, treatment codes, conversion ratios Tech Stack: Python, Random Forest, scikit-learn, pandas, feature engineering
Business Value: Direct cost reduction through feed optimization, improved production efficiency, and data-driven decision making in commercial poultry operations.
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Posted Jul 28, 2025
ML system predicting daily feed consumption for Cobb 500 chickens. 99%+ accuracy helping poultry farms optimize feed costs and production efficiency.
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Nov 2, 2022 - Apr 16, 2023
