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Final Projects!

posted May 13, 2014, 11:47 AM by Jen Mankoff
I was planning on featuring just a few final projects, but you all blew me away yesterday, so I'm posting links to everything. Here's the lineup:

- Visualizing Differences in Aggressive Driving Behavior. I like the fact that this gives me a totally new perspective on driving. 
- Github Archive Explorer set up to look at my brother's github account (he's much more active than me :). A beautifully linked set of visualizations. I like the fact that the data set is so large that I can look myself up in it :).
- An exploratory analysis of Twitter hash tags which lets you see which tags are 'colocated' within tweets. I like the fact that I can enter a tweet and get live response from current tweets.
- The fMREYE system for brain data visualization. I like the fact that this is designed for real use and already up and running.
- The Indian Election tweet visualizer which lets us explore sentiment by politician and city. I like the fact that this is so well connected to an interesting and relevant set of user needs. 
- The Yelp treemap and tag cloud visualizations let us explore what people talk about in reviews of different Yelp categories. I like the fact that this helps to expose the diversity of what's on Yelp.
- The Yelp Insighter helps potential business owners to explore the types of restaurants already up and running in the area and how they are doing. I like the fact that this provides so much guidance to the user. 
- The San Francisco Movie Tourist Guide lets you explore the locations and history of movies shot in SF. I like the fact that this is so connected to a real passion of its creators. 
- The AppTrack android app (Install link) and an example of the web data overview view for it's author's use data. I like the fact that this project involved a deployed mobile app and live data collection from unknown users. This is risky and difficult.
- The Natality Trends project explores data sets that may affect birth rates in the US. I like the fact that this project drew from so many different data sets to answer its questions.
- The loan analysis project presents a predictive algorithm for predicting when loans will default. I liked the carefully documented approach to using machine learning in this project.
- The DVD release strategies project explores the impact of DVD release timing on pirating of movies. I like the mixed methods approach here which uses regression not only to make predictions but also to explore various factors. 
- The Job Search app does a great job of allowing people to explore how different jobs perform on various metrics of interest across the country. I like the fact that it is a real world problem and a very rich set of visualizations for exploring the data.