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📚 Project Name: Optimized Diabetes Prediction with Ensemble Models | Machine Learning

1️⃣ Data Handling: Imported data using pandas, a powerful data manipulation library in Python. 🐼

2️⃣ Modeling: Utilized ensemble models and oversampling techniques to enhance model performance, achieving a test accuracy of 0.83. 🎯

3️⃣ Hyperparameter Tuning: Utilized GridSearchCV for hyperparameter tuning, resulting in a significant improvement in model accuracy of 15%. 🔍

4️⃣ Deployment: Deployed the predictive model as an API using FastAPI and hosted it on Heroku, enabling real-time predictions for users. 🚀

This project showcases skills in machine learning, data handling, model optimization, and deployment! 👏

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