Working with Citi Bike trip data, I used machine learning tools to predict trip generation from hypothetical Citi Bike stations across New York City. The final product is an interactive R Shiny web application which visualises the trip generation predictions spatially and allows users to query any location to obtain a prediction from the model.

In this project, I web-scraped parliamentary speeches from Singapore and applied topic modelling techniques to the speeches given by each member of parliament (MP) to identify distinct topic clusters, and then visualised it in two dimensions using an interactive plot on Python.