Portfolio
A collection of my work in data science, machine learning, and full-stack development.
Tinnitus Detection Using Machine Learning
Developed a predictive model to classify tinnitus presence using extracted features from patient data. Built and evaluated multiple ML algorithms (SVM, Random Forest, Logistic Regression), implemented SMOTE, and achieved strong performance.
ECG Heartbeat Classification
Applied ML techniques to classify arrhythmia patterns on medical data. Developed automated preprocessing pipeline for signal segmentation and tested models including CNN-based approaches.
Violent Crime Big Data Analysis
Processed and analysed multi-million-row datasets (65M+ Rows) using PySpark and Azure Databricks. Built automated ETL pipeline and delivered insight dashboards for regional crime trends.
TravelNorth Database Analytics Project
Constructed EER diagrams, conceptual models, and SQL-based analytical solutions. Delivered optimised queries and a working data warehouse structure.