About Me
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Passionate about leveraging Artificial Intelligence and Machine Learning to solve real-world problems and create innovative solutions.
Built a full-stack disease risk prediction web app using Flask with 15+ clinical features. Trained and optimized the model on a dataset of 20,000 patient records, achieving 89% accuracy, and integrated it into Flask for real-time predictions.
Built a telecom customer churn prediction web app using Flask and Scikit-learn. Trained on 10,000 records with tuned classification models, achieving 96% accuracy, and added SHAP-based insights to explain key factors behind churn predictions.
Built an NLP-based fake news detection system using TF-IDF and machine learning with scikit-learn, pandas, and NLTK. Trained and evaluated the model end-to-end, then deployed it using FastAPI as a REST API to deliver real-time predictions for external applications.
I'm always open to discussing new projects, creative ideas, or opportunities to be part of your vision.