Semantic Network Analysis of Ideological Communities on Twitter

| By Logan Wilson | Introduction One of the primary contributions of Twitter to modern media is the notion of the “hashtag” – a single word or phrase that captures an idea, concept, or movement. As more and more people see and share the hashtag, the movement grows and evolves, giving way to new ideas

Real-Time Human Activity Classification in Videos

| By Daniel Lütolf-Carroll and Rishabh Joshi | Problem Statement Deep Learning has been applauded for its versatility and applicability on many use-cases across industries. We set out to explore and familiarize ourselves with DL on a problem that was relatable to most: video streaming. Our project aimed to enhance the user viewing experience by

Chicago Botanic Garden: Members Relationship Management Project

| By Ethel Shiqi Zhang | As students in the Master of Science in Analytics (MSiA) Program, we are given a plethora of opportunities to engage with clients to apply our newly-minted analytics skills by tackling real-world problems. This year, a group of four students paired up with IBM Analytics to carry out a project

Running a Marathon in 45 Seconds Flat

| By Chris Rozolis | I should start by saying I have absolutely no long-distance training experience and have never completed a marathon, half-marathon, or even a 5K in my life — that being said, I have experience in running marathons…or at least simulating the running of them using Python. Over the past 8 months

Movie Recommender System Based on Natural Language Processing

| By Kehan (Eric) Pan | Introduction Natural Language Processing (NLP) is rarely used in recommender systems, let alone in movie recommendations. The most relevant research on this topic is based on movie synopses and Latent Semantic Analysis (LSA) .However, the prediction power is far from satisfactory due to the relatively small average size of

DJ Random Forest: Song Recommendations through Machine Learning

| By Logan Wilson | Where do you find new music? If you’re listening to post-grunge on your Sony Walkman, congratulations, you’re still in 1999! You discover new music primarily through the radio, at the mercy of disk jockeys playing actual disks, or by wandering aimlessly around record stores, hoping to be inspired by some

A Hybrid Recommender System for Destiny and eSports

| By Kevin Zhai | For the full paper, click here. Introduction While the obvious applications of data science are domains like healthcare and financial services, the world of video games is ripe for advanced analytics. Gaming is a large industry, with $101 billion worldwide revenue in 2016 [1]. Compare this with the $38 billion

Learning to Fight: Deep Learning Applied to Video Games

| By Dr. Ellick Chan | Artificial Intelligence (AI) is commonly used in video games to control non-human “computer” players. The AI used in video games often relies only on simple logic and heuristics, so “computer” players do not always have human-like playstyles. This is unfortunate because games that feature human-like AI could be very popular

Explaining the inner workings of Deep Learning

| By Dr. Ellick Chan | MSiA students are helping lead the way toward building more reliable deep learning AI models by making them explainable. This Spring, 9 student groups developed ways to “peek into” models built for their projects. In previous years, students were able to do impressive work in their projects, but they were