Hi, I'm Aamir Imam

Built a full-stack Expense Tracker using the MERN stack, featuring JWT authentication, monthly income/expense tracking, budget limit setting, and interactive data visualizations through dynamic charts.

Implemented a smart budget optimization system that analyzes user spending patterns and provides real-time alerts and suggestions to help users manage finances more efficiently.

Built a robust time-series pipeline to forecast 7-day energy demand using ARIMA, SARIMA, Exponential Smoothing, and GARCH models on AEP hourly data for accurate energy consumption forecasting, enhancing decision-making with predictive analytics.

Designed an interactive Streamlit dashboard to visualize load and volatility forecasts, enhancing short-term planning with real-time insights. Also trained the dataset upon various time-series models.

Developed a machine learning-based disease prediction system using blood sample data, evaluating models such as Logistic Regression, Decision Tree, Gradient Boosting, and XGBoost. Comprehensive performance analysis revealed XGBoost as the most accurate, achieving ~98% accuracy.

Implemented the XGBoost prediction model, serving as the core component for the disease prediction system with plans for further integration and deployment.