Car Insurance Claim Prediction

I developed machine learning models (Logistic Regression, Decision Trees, kNN, Random Forest) to predict insurance claim likelihood, optimizing risk assessment and pricing strategies for a car insurance company. This work enhanced my understanding of predictive modeling in the insurance industry.

Predicting Airbnb Prices in New York City

I predicted room rates using machine learning models (linear regression, decision tree, kNN, and random forest) on a dataset of 42,000+ Airbnb listings and 18 variables, analyzing factors like location and host details to assess model effectiveness in capturing room rate influences.

Application of Vehicle Routing Problem for A Convenience Store Chain Delivery Service Using Exact Algorithm

I applied the Vehicle Routing Problem (VRP) to optimize delivery services, employing an exact algorithm and leveraging IBM CPLEX to determine the most efficient route with minimum distance.

Analysis of Delinquency in theCredit Card Segment in the USA

I created a Tableau dashboard to analyze the impact of socioeconomic factors on credit card delinquency, uncovering key insights on the correlation between variables like unemployment, income, cost of living, age, and interest rates.

Classification - Loan Approval Predictions

I developed predictive models to automate the loan eligibility process, improving decision-making accuracy. Through feature analysis, I identified key factors influencing loan approvals and tested classification models like logistic regression and decision trees to optimize predictions.

Simio Business Case Competition 2022

I conducted analysis and simulation of over 5,000 data points with Microsoft Excel and Simio in 4-person team, resulting in the development of an optimized transportation model for oil rig operations. These recommendations led to a significant cost reduction of 36.1%.

SKILLKAMP Business Case Competition 2023 by Kasikorn Bank

I extracted business insights through the analysis of shopping orders dataset, harnessed PowerBI for data visualization, and devised profit-enhancing recommendations for the company.

Naïve Bees: Predict Species from Images

I developed a machine learning model using Python and the Pillow image library to distinguish between honey bees and bumble bees, contributing to improved field data collection for researchers.

The GitHub History of the Scala Language

I analyzed Scala's development history on DataCamp using Git and GitHub data. I cleaned, visualized, and interpreted 30,000+ commits spanning a decade.

Chulalongkorn Engineering’s Internship Website

I Collaborated within a 5-person team to utilize SQL and HTML for data organization and to design an optimal user interface. This initiative focused on presenting internship positions on the website and seamlessly integrating the university database with student applications.