In this talk, "Using Go for Statistical Programming," Aditya Mukerjee, student at Cornell Tech, discusses how to use Google's Go programming language for statistics. This talk was recorded at the New York Open Statistical Programming meetup at Knewton.
While R is the language of choice for academic statisticians, data scientists sometimes use other languages and frameworks for advantages such as distributed computing, speed, and portability. Go, a new language developed by Google, provides a convenient alternative for statistical work, with built-in concurrency features and a focus on both speed and stability. In this talk, Aditya will provide an overview of the current state of statistical programming in Go, and some basic tips for getting started.
Aditya graduated from Columbia University with a degree in CS and statistics, and was a hackNY Fellow (class of 2011). Previously, he worked on the data team at OKCupid providing research for OKTrends posts, and on the server team at Foursquare, working on the Foursquare Explore recommendation engine. Currently, he attends Cornell Tech.
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How we use Go and MongoDB
In this talk, we'll hear from Sam Helman, Software Engineer at MongoDB (formerly 10gen), on how MongoDB is integrating Go into their new and existing cloud tools. Some of the tools leveraging Go include the backup capabilities in MongoDB Management Service and a continuous integration tool. They see using Go as an opportunity to experiment with new technologies and create a better product for end users. This talk was recorded at the MongoDB User Group meetup at MongoDB.