Master Thesis: Opinion Mining in an Industrial Context

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.

Route Suggestion with Real-Time Streamed Data

Project of big data to use real time simulated (SUMO) traffic data streamed by rotating Kafka topics. The objective was to assist the emergency respondent team to reach their destination in a more efficient way, by taking the current traffic status into consideration.

Kickstarter Pledge Dashboard

Visualisation project on utilising the open data from Kickstarter in a dashboard for analysis on pledged amount on category – and sub-category level.

US Airline Tweet Sentiment

Project on processing documents of short text with the objective of assigning sentiment class; negative, neutral and positive

Visualisation of Airport Connectivity

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.

Gender Gap Investigation

An experiment into using multiple learning algorithms on the problem of predicting the gender gap of a country from women rights data.

Image Mosaic

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.

Emotions by Musical Cues

Project in cognitive science trying to predict what the associated emotion will be based on the components used in the song.

Algorithm Implementation

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.

Photometric stereo

Task to generate depth maps from pictures that are all taken from the same direction, but under different lighting conditions.