In this post I will go through some of the things I did in my master thesis project in the field of Natural Language Processing. Includes extensive pre-processing, and the application of state-of-the-art topic modelling and text classification.
Visualisation project on utilising the open data from Kickstarter in a dashboard for analysis on pledged amount on category – and sub-category level.
Project on processing documents of short text with the objective of assigning sentiment class; negative, neutral and positive
A visualisation depicting the connectivity of airports around the world. Objective is to get an overview of what airports are more connected, or to what cluster of airports they are most connected to.
An experiment into using multiple learning algorithms on the problem of predicting the gender gap of a country from women rights data.
Python project on creating a mosaic of a collection of images by matching tiles of an original image through different feature definitions. In IPython Notebook format.
Project in cognitive science trying to predict what the associated emotion will be based on the components used in the song.
Implementation of few basic machine learning algorithms. Frequent pattern mining in the form of Apriori. Supervised classifier in the form of K-Nearest Neighbour. Unsupervised clustering in the form of K-means clustering.
Task to generate depth maps from pictures that are all taken from the same direction, but under different lighting conditions.