// Data Science & AI
Computer Science student at Taylor's University specialising in Data Science and AI. My main interest is in building ML models, analytics dashboards and turning raw data into actionable insights.
I'm a final-year Computer Science student at Taylor's University, specialising in Data Science with an extension in Artificial Intelligence. I'm passionate about building models that solve real problems from detecting bone fractures in X-rays to predicting loan defaults.
Beyond ML models, I also build full stack applications such as my Final Year Project called MediVision, which is a Smart Patient Flow Platform for hospital emergency departments.
I'm very much passionate about AI and turning complex data challenges into impactful solutions.
MediVision is a full-stack hospital emergency department patient flow management system built to streamline hospital pathway, triage and clinical decision-making in real time built by a team of 5 members for our Final Year Project (Capstone Project).
Fine-tuned EfficientNetB0 (transfer learning) with OpenCV/CLAHE preprocessing and Grad-CAM interpretability to automatically detect bone fractures in X-ray images. Trained on 4,083 real hospital X-rays.
Built two text classification models on 53K+ mental health statements and compared Decision Tree vs Neural Network performance.
Performed sentiment analysis using a Bidirectional LSTM model on IMDB movie reviews in Google Colab. Binary classification of positive vs negative reviews.
Built data mining models on drug-death records. Applied Random Forest for classification, K-Means for seasonal clustering, and Isolation Forest to detect geographic outliers.
Developed ML models to analyse loan default risk on a financial dataset. Compared k-Nearest Neighbours against Decision Tree classifiers on key financial features.
Built an IoT prototype using ESP32 and Raspberry Pi with sensors to automate plant watering and monitor moisture, temperature, humidity, and soil pH in real time.
Conducted EDA and preprocessing on the UCI Heart Disease dataset using Python and Scikit-learn. Developed a Logistic Regression model to predict heart disease risk.
Feel free to reach out & let's connect!