Presented By
O’Reilly + Cloudera
Make Data Work
March 25-28, 2019
San Francisco, CA
Robert Horton

Robert Horton
Senior Data Scientist, Microsoft

Website

Bob Horton is a senior data scientist on the user understanding team at Bing. Bob holds an adjunct faculty appointment in health informatics at the University of San Francisco, where he gives occasional lectures and advises students on data analysis and simulation projects. Previously, he was on the professional services team at Revolution Analytics. Long before becoming a data scientist, he was a regular scientist (with a PhD in biomedical science and molecular biology from the Mayo Clinic). Some time after that, he got an MS in computer science from California State University, Sacramento.

Sessions

11:00am–11:40am Wednesday, March 27, 2019
Building high-performance text classifiers on a limited labeling budget
Data Science, Machine Learning & AI
 Location: 2010
Secondary topics:  AI and Data technologies in the cloud, Text and Language processing and analysis
Robert Horton (Microsoft), Mario Inchiosa (Microsoft), Ali Zaidi (Microsoft)
Average rating: ****.
(4.70, 10 ratings)
Robert Horton, Mario Inchiosa, and Ali Zaidi demonstrate how to use three cutting-edge machine learning techniques—transfer learning from pretrained language models, active learning to make more effective use of a limited labeling budget, and hyperparameter tuning to maximize model performance—to up your modeling game. Read more.