Automatic MCMC hyperparameter sensitivity measurements in Stan

Ryan Giordano / January 19, 2018

A Bayesian approach to statistical modeling comes with many advantages. For example, it's the only logically coherent way to model uncertainty of parameter estimates! Being Bayesian has never been easier than it is now, thanks to high-quality, easy-to-use automatic tools like Stan.

Data Science Discovery Program (formerly known as the BIDS Collaborative) Launches New Plans and Projects for Spring 2018

Marsha Fenner / January 18, 2018

The newly-launched Data Science Discovery Program (formerly known as the BIDS Collaborative) provides undergraduates with opportunities to engage in hands-on, team-based research opportunities by connecting them with cutting-edge data science research projects, community impact groups, entrepreneurship ventures, and educational initiatives across UC Berkeley. 

BIDS' Karthik Ram receives NSF award to design "US Research Software Sustainability Institute" (URSSI)

Marsha Fenner / December 21, 2017

BIDS Research Scientist Karthik Ram has been awarded NSF funding to lead a project toward designing and creating the US Research Software Sustainability Institute (URSSI), a community hub that will provide services to help scientists create improved, more sustainable software.

2017 TextXD Conference - Videos and Commentary

Marsha Fenner / December 2, 2017

  THURSDAY, NOVEMBER 30 at BIDS (190 Doe Library) Host Nick Adams, a researcher at BIDS and founder of GoodlyLabs, welcomed this year's participants. 10:10-10:35 AM John Mohr, University of California, Santa BarbaraThe Frontiers of Social Scientific Text Analysis

Binder 2.0 has arrived!

Chris Holdgraf / November 30, 2017

The Berkeley Institute for Data Science (BIDS) is pleased to announce the release on Binder 2.0! Binder is a collection of technology that makes it easy to create sharable, interactive computing environments that run in the cloud. It makes it possible to run a server that enables users to specify their computational environment with commonly-used text files (such as requirements.txt for python users).

Berkeley team wins Citadel's "Data Open" Championship

Marsha Fenner / November 29, 2017

BIDS Graduate Fellow Sören R. Künzel and his fellow UC Berkeley team members have been awarded the top prize in Citadel's Data Open datathon championship.