Automatically Making Sense of Data
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While the availability and size of data sets across a wide range of sources, from medical to scientific to commercial, continues to grow, there are relatively few people trained in the statistical and machine learning methods required to test hypotheses, make predictions, and otherwise create interpretable knowledge from this data. But what if one could automatically discover human-interpretable trends in data in an unsupervised way, and then summarize these trends in textual and/or visual form?
To help make progress in this area, Professor Zoubin Ghahramani and his group at the University of Cambridge received a Google Focused Research Award in support of The Automatic Statistician project, which aims to build an “artificial intelligence for data science”.
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