There are 3 data science projects in this repository.
Vizbud is a travel recommendation tool that suggests points of interest (POIs) to its users for their vacation. The system suggests POIs to the user based on places visited by their friends/friends of friends with similar levels of travel preference. We implement our system based off the data from a social media platform called Gowalla. Specifically, the system will study the user’s preferences, friendship network and then suggest a few cities containing some of the spots that the user might want to visit next.
This project we explore two different algorithms to achieve our goal. The first approach uses the traditional Collaborative Filtering method to recommend spots based on users in the entire social media dataset who are very similar to the user in terms of travel preferences/interests. Our second approach uses Graph Mining to recommend a city and its spots based on the user's friendship network who are socially similar to the user. Finally, we attempted to combine both approaches to recommend places based on users' friends that are socially similar and has simliar interest as the user. Detailed explanation on all the approaches will be later discussed in this report.
Airline Passenger Satisfaction - Data Analysis/Visualization and Predictive Modeling (Python, Jupter Notebook)
Airline passenger satisfaction is critical for customer retention and business growth. This project begins with descriptive analytics to explore and visualize key factors influencing satisfaction, such as seat comfort, service quality, food, and check-in experience.
Using predictive analytics, classification models (Logistic Regression, Random Forest, XGBoost) will predict passenger satisfaction, identifying the most influential factors and creating models that could predict passenger satisfaction.
In part II, we plan to use prescriptive analytics to optimize resource allocation using linear programming to maximize satisfaction within budget constraints. For example, determining whether to invest more in seat upgrades or customer service training. The goal is to enhance passenger experience, improve satisfaction rates, and drive long-term profitability through data-driven decision-making.