I am a Data Science and Analytics student from NUS. I'm interested in how data is used to form meaningful conclusions and make appealing visualizations. I am familiar with Python, SQL, R , Excel and Java as well as several Machine Learning techniques.
I am always open for internship opportunities, get in touch with me using one of the links below!
Major in Data Science and Analytics
Minor in Japanese Language
Extracurricular Activities
-Member of the College Basketball Team
Played in National Inter-School Basketball Tournament
-Member of the Earth Society
Participated in Food Waste Recycling Programme
Participated in visits to Lions Home for the Elderly
Created and maintained reports and dashboards in Salesforce to track key performance indicators and measure business success
Improved company processes by automating data preprocessing using Pandas, which resulted in more efficient data analysis and reporting
Developed a diverse set of skills in data analysis, data management, and data visualization
Responsible for the operation and maintenance of main gun as well as all armaments and ammunition on board ship.
Planned sporting events for the unit including representing the unit in coordinating the SAF wide charity event ‘SAFRA swim for hope 2019’, on top of conducting IPPT and sporting events with vendors.
Coordinated functions as well as sports competitions not only within the unit but with foreign Navies as well.
Some personal as well as academic projects thats showcase what I have learnt as a Data Analyst
SharenStay Home Sharing App
Skills Learnt: SQL, Flask, Docker, HTML, CSS, UX, Website Creation & Design
Description: This project is a Home Sharing app on Flask that hosts data from a database of all houses available for rental in Singapore. Users can view, filter and make bookings on this website.
Anime Recommender System
Skills Learnt: Machine Learning, Collaborative Filtering, Scikit Learn, Singular Value Decomposition
Description: This machine learning project explores the development of recommendation systems using both factor and non-factor models. It discusses the use of content-based filtering, collaborative filtering, and hybrid systems as alternatives to factor models.
Music Popularity Prediction Using Machine Learning Techniques
Skills Learnt: Machine Learning, Random Forest, Linear Regression, Support Vector Machines (SVM), XGBoost in R, Model Evaluation
Description: In this project, we aim to predict the popularity of a song based on its features using various machine learning models. We will obtain the feature importance coefficients to determine what makes a popular song.
Image Classification using Machine Learning
Skills Learnt: Neural Network training and Optimization, Flax, Scikit, Data Preprocessing, Data Visualization, JAX
Description: This image classification project involves the training of a Neural Network. Evaluating lightweight CNN architectures like LeNet and AlexNet, it employed the AdamW optimizer to address generalization issues. Batch sizes balanced convergence speed and performance. Data augmentation with Albumentations enhanced dataset diversity.
Predicting Video Game sales using Machine Learning Models
Skills Learnt: Exploratory Data Analysis, Statistical Methods, Prediction, Model Evaluation, XGBoost, Clustering, Regression
Description: This project predicts video game sales using machine learning models such as XGBoost and Kmeans Clustering, as well as linear regression to analyze the dataset and provide insights into the gaming industry.
Elderly Fall Detection using Machine Learning
Skills Learnt: TensorFlow, Scikit Learn, Computer Vision, Convolutional Neural Networks
Description: This project aims to develop a vision-based fall detection monitoring system using Neural Networks for elderly' use, detecting falls to alert caregivers.
Flight Delay Modelling using SQL and Docker
Skills Learnt: Docker, AWS, Regression(Machine Learning), Backend Development, Frontend Development
Description: Project in a team of 8 to model feature importance for flight delays and create an app for air traffic controllers. This showcases the full Data Science Life Cycle of a project.
This Website!
Skills Learnt: HTML, CSS, Bootstrap, UX Design, Backend Development, Frontend Development
Description: I've crafted a portfolio website using Bootstrap, CSS and HTML that effectively showcases all my projects and offers a convenient way for potential employers to reach out to me. Thanks to Netlify, the website is continuously hosted live, ensuring it's always accessible and ready for engagement.
National University of Singapore (Centre for Language Studies)
