Computer Science Graduate
BSc (Honours) Computer Science student specializing in Machine Learning & AI. Deeply curious about building intuitive, efficient applications and leveraging data to uncover meaningful insights. Always eager to learn, improve, and take on new challenges.
Interests: Data Analysis, Data Engineering, Data Science, Software Development, Full-stack development, Machine Learning, Computer Vision
Project focuses on the development of a robust and accurate system for detecting brain tumors from MRI scans using advanced deep learning techniques. The core of the project leverages Convolutional Neural Networks (CNN) and U-Net models to achieve high precision in tumor identification and segmentation.
Machine Learning Artificial Intelligence Python Models Deep Neural Networks CNN U-Net VGG16 TensorFlow Keras OpenCV Deep Learning Medical Imaging Brain Tumor Detection AI in Healthcare
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Utilize the implemented genetic algorithm (GA) to optimize the performance of virtual creatures in a simulated environment designed to mimic the challenge of climbing a mountain. Inspiration is taken from Karl Sims Creatures. A standout example of applying evolutionary principles to solve optimization challenges in a creative and engaging way.
Artificial Intelligence Python PyBullet Ipython Evolution Theory Fitness Function Genetic Algorithm (GA) Virtual Creatures Optimization Evolutionary Computing Machine Learning Artificial Life Simulation
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Resume Classification Using Statistical and modern Deep Learning Models.
Statistical Models Deep Learning Resume Classification Natural Language Processing (NLP) Text Preprocessing Embedding-Based Models Convolutional Neural Network (CNN) Long Short-Term Memory (LSTM) Recruitment Automation Bias Reduction Feature Engineering Sequential Data Analysis Deep Learning Text Classification
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Projects included carrying performance comparison of classification algorithms such as k-Nearest Neighbors (kNN), Naive Bayes, and Decision Trees in accurately predicting the presence or absence of diabetes. In additon, applied deep learning techniques to accurately classify hand movements from photographs, contributing to the field of sign language recognition.
Machine Learning Classification Python Models Artificial Neural Networks Scikit Learn
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Analyzed and modeled the Graduate Employment Survey (GES) dataset, specifically for universities in Singapore.
Database Development ER Diagrams SQLite MySQL Relational Schema Data Normalization SQL Queries Node.js Web Application
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This project focuses on analyzing the used cars market to identify trends, correlations, and influential factors affecting the selling prices of used cars. It employs statistical and machine learning techniques to build predictive models and extract actionable insights for the automotive resale market.
Data Preparation Feature Engineering Exploratory Data Analysis (EDA) Statistical Analysis Data Visualization Correlation Analysis Predictive Modeling Feature Importance Polynomial Features Model Evaluation Hyperparameter Tuning
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This project implements a computer vision-based traffic monitoring system to count and track vehicles in real-time video feeds. By using frame differencing and background subtraction techniques via openCV, the system accurately detects moving vehicles and calculates traffic flow rates. Key features include a configurable region of interest (ROI), dynamic buffer time to prevent double counting, and a real-time display of vehicle count and traffic rate.
OpenCV Computer Vision Python
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Implemented a Node.js-based web application that interacts with an SQLite3 database. It allows users to publish and read articles through a web interface. The application includes a password-protected authoring section and a reader section for accessing published content.
Database Development SQLite MySQL ER Diagrams Node.js
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This group project utilized agile methodologies in developing a mobile app for pet owners that integrates all essential features for managing pet care. The app utilizes an SQL database for data management and is built using React. The app offers a complete solution for pet care management.
Agile React SQL Database CMS HTML CSS Tailwind Kanban
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This project aimed to uncover meaningful insights about industries and their workforces using exploratory data analysis (EDA). By leveraging real-world data on industries, companies, and workforce dynamics, I sought to answer several key questions to better understand industry trends, company ratings, job markets, and salaries.
Exploratory Data Analysis Dataset Exploration Industry Trends Workforce Insights Company Ratings Business Intelligence Data-Driven Decisions Industry Analytics
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