The What-If Tool: Interactive Probing of Machine Learning Models

1 code implementation • 9 Jul 2019 • James Wexler, Mahima Pushkarna, Tolga Bolukbasi, Martin Wattenberg, Fernanda Viegas, Jimbo Wilson

A key challenge in developing and deploying Machine Learning (ML) systems is understanding their performance across a wide range of inputs.

BIG-bench Machine Learning Fairness

Scalable and accurate deep learning for electronic health records

no code implementations • 24 Jan 2018 • Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M. Dai, Nissan Hajaj, Peter J. Liu, Xiaobing Liu, Mimi Sun, Patrik Sundberg, Hector Yee, Kun Zhang, Gavin E. Duggan, Gerardo Flores, Michaela Hardt, Jamie Irvine, Quoc Le, Kurt Litsch, Jake Marcus, Alexander Mossin, Justin Tansuwan, De Wang, James Wexler, Jimbo Wilson, Dana Ludwig, Samuel L. Volchenboum, Katherine Chou, Michael Pearson, Srinivasan Madabushi, Nigam H. Shah, Atul J. Butte, Michael Howell, Claire Cui, Greg Corrado, Jeff Dean

Predictive modeling with electronic health record (EHR) data is anticipated to drive personalized medicine and improve healthcare quality.

No Classification without Representation: Assessing Geodiversity Issues in Open Data Sets for the Developing World

no code implementations • 22 Nov 2017 • Shreya Shankar, Yoni Halpern, Eric Breck, James Atwood, Jimbo Wilson, D. Sculley

Further, we analyze classifiers trained on these data sets to assess the impact of these training distributions and find strong differences in the relative performance on images from different locales.

General Classification