Explore a selection of my practical and academic projects in machine learning, software engineering, and system design.
Developed a full-stack group project web application that allows users to book doctor appointments, join health-related communities, and engage in real-time medical discussions — aimed at improving healthcare accessibility and community support.
Collaborated on a group project during my Bachelor's in Computer Science and Software Engineering to train and deploy a facial image recognition model using XGBoost and TensorFlow. Leveraged Python and scikit-learn to optimize model performance and ensure reliability, achieving high accuracy.
Using a public dataset from Kaggle, this project applies various classification algorithms like Logistic Regression, Decision Trees, and Random Forests to predict a patient’s heart disease risk. Users can input health metrics and receive a risk assessment on the UI powered by Streamlit.
This regression-based ML project estimates vehicle prices from input features like model, mileage, and engine type. The pipeline includes data cleaning, exploratory analysis, and model tuning. It's wrapped in a user-friendly interface for trying out real car data and getting predictions.