A supervised machine learning model that predicts the likelihood of diabetes in patients based on diagnostic measurements. Built using classification algorithms including Logistic Regression, Decision Trees, and Random Forest. The model was trained on the PIMA Indians Diabetes dataset and achieves strong accuracy through feature engineering and hyperparameter tuning.
A full-stack E-Learning website built to make quality education accessible and interactive. Eudify features course listings, user authentication, progress tracking, and a clean modern UI. Built with HTML, CSS, JavaScript on the frontend and PHP on the backend, with a structured database layer for content management.
A comprehensive analysis and prediction model focused on identifying the presence and risk factors of heart disease in patients. The project combines exploratory data analysis with multiple classification models to uncover key patterns in cardiovascular health data. Visualizations were built to communicate findings clearly, making the model insights interpretable for non-technical stakeholders.