📚 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! 👏