This past Tuesday, Knewton hosted one of NY’s most intense machine learning/big data events of the year. Over 100 people came out to mingle and listen to an awesome lineup of speakers. If you have the time, check out the full recording:
Otherwise, here’s a quick look at what went down.
The evening was kicked off by one of Knewton’s lead data scientists, George Davis. George talked about how Knewton develops scalable statistical models of the learning process in order to inform recommendations around supplementary content and study groups.
Next up was John Myles White, author of Machine Learning for Hackers. He reviewed the basics of machine learning and showed us how simple methods developed by researchers can be treated as black-box function calls by using existing languages like R and Python. In his talk, John also worked through the intuitions behind linear regression, logistic regression, and k-nearest neighbors to show how they might be applied in common situations like spam classification.
Wiqar Chaudry, the Director of Product Management at NuoDB capped off the evening with a discussion of cloud computing, fast machines, and the proliferation of mathematics and programming in today’s society.
A big thanks to NY Software Engineers and organizer, Michael Latulippe for bringing everyone together for this memorable event.