Under the ETICC program, I collaborated with a Birmingham startup to develop a state-of-the-art market research prototype. By aggregating diverse data sources, this system generates invaluable marketing insights. The work done on this project led to the composition of my Master's thesis at Aston University, in the UK.
1. Crafted a comprehensive full-stack web application, leveraging TypeScript/Aurelia for the frontend and Python/Django for the backend.
2. Designed advanced forecasting for nonstationary marketing data using kernel machines, particularly the KRLS-T model, yielding precise predictions.
3. Implemented a meticulous k-means clustering algorithm that can accurately classify products.