Is a movie review positive or negative? Five different classifiers decide

As part of the Machine Learning in Practice course at Radboud University, I took part in two Kaggle competitions in a team with five other students. This blog will revolve around the competition called Bag of Words Meets Bags of Popcorn.   “Is AI a bad thing?” This competition concerned sentiment analysis of movie reviews. … Continue reading Is a movie review positive or negative? Five different classifiers decide

Can computers replace teachers? Automatically grading exams with vector space models

Below you can see two pictures of me. In the left one, I’m grading a big pile of student papers, feeling stressed and tired. Imagine how nice it would be if I could let my computer do all of this work, so that I can spend more time relaxing with my cat like in the … Continue reading Can computers replace teachers? Automatically grading exams with vector space models

Named Entity Recognition (NER): Extracting a timeline from biographical texts

Texts written in natural language are generally unstructured, meaning that they are not organized in a pre-defined structure, such as a table. Rather, writers often mean to tell a story, and let their text flow freely in sentences and paragraphs. While such texts typically are more fun to read, the information they contain is not … Continue reading Named Entity Recognition (NER): Extracting a timeline from biographical texts

Who wrote this text? Authorship attribution with SVM

Authorship attribution is the task of detecting who has written a certain text. As a famous example, researchers unmasked crime writer Robert Galbraith in fact to be J.K. Rowling, the writer of the Harry Potter books. In this blog post, I will explore and explain the use of the support vector machine (SVM) classification algorithm … Continue reading Who wrote this text? Authorship attribution with SVM