Welcome to Analyze Boulder 51!
Analyze Boulder is a community of data geeks who live, work, and play in Boulder, Colorado.
The first Wednesday of every month, our members give fast, accessible, high-energy TED-style talks once a month on any data topic. Contact us (http://speakers.analyzeboulder.com/) if you want to present at a future event.
We start with social time / beer from 6-6:20pm, followed by the live event, and then we stick around and chat over beers afterwards. You can also join the event via our live stream (see below).
Please bring cash to contribute for beer. We are working on our lineup, but here's what we have so far:
Julia Richman from the City of Boulder Innovation and Analytics Office returns to update us on the city's strategy for data and engagement.
Sam Zhang analyzed the front pages of print newspapers from the Newseum website by scraping PDFs, extracting bounding boxes, font sizes, etc., and creating a structured database. He'll show us some neat visualizations on the results.
Ky Kiefer shares an open-source Python project aimed at predicting depression from acoustic features in speech, based on underlying differences in acoustic features between depressed and non-depressed individuals. Speech can be represented in ways learnable by machine learning algorithms that have promising predictive power in catching early stage depression.
Join the Live Stream Here at 6:20 PM MST