neamadarwesh02-ops/Veterinary-Diseases-Analysis-Egypt

Veterinary Disease Outbreak Analysis in Egypt using Machine Learning # Veterinary Disease Outbreak Analysis in Egypt ## 📌 Project Overview This project analyzes veterinary disease outbreaks in Egypt and predicts economic losses using Machine Learning models. The goal is to: * Identify most common diseases * Analyze outbreak trends * Predict economic losses * Compare Machine Learning models * Build data-driven insights for veterinary decision making --- ## 📊 Dataset Features * Farm_ID * Governorate * Animal_Type * Farm_Size * Disease_Detected * Vaccinated * Outbreak_Cases * Deaths * Vet_Visit * Treatment_Used * Economic_Loss_EGP * Month --- ## 🔍 Project Workflow 1. Data Cleaning 2. Exploratory Data Analysis (EDA) 3. Feature Engineering 4. Model Training 5. Model Evaluation 6. Model Comparison 7. Advanced Analysis (SHAP, PDP) --- ## 🤖 Machine Learning Models Used * Linear Regression * Decision Tree * Random Forest * Support Vector Machine (SVM) --- ## 📈 Key Insights * Poultry farms had highest outbreak rates * Avian Influenza caused highest economic losses * Vaccination significantly reduced deaths * Random Forest achieved best performance --- ## 📊 Model Performance | Model | Performance | | ----------------- | ----------- | | Linear Regression | Baseline | | Decision Tree | Good | | Random Forest | Best | | SVM | Moderate | --- ## 🛠 Tools & Technologies * Python * Pandas * Scikit-learn * Matplotlib * Seaborn * SHAP * Power BI --- ## 📁 Project Structure See folders for: * Data * Notebooks * Source Code * Reports * Dashboard --- ## 🚀 Future Work * Deploy model * Real-time prediction * Dashboard automation --- ## 👩‍💻 Author Neama Darwesh Data Analyst | Machine Learning Enthusiast ---