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Astronomers deal with huge datasets, and they are about to get even bigger with the construction of the Vera Rubin Observatory. When you can detect a million supernovae per year, how do we make sense of this data and decide which ones are the "most interesting" to study? Professor Ashley Villar at the Center for Astrophysics | Harvard & Smithsonian has made her career out of developing machine learning techniques to answer this very question.
By Paul Duffell4.4
5252 ratings
Astronomers deal with huge datasets, and they are about to get even bigger with the construction of the Vera Rubin Observatory. When you can detect a million supernovae per year, how do we make sense of this data and decide which ones are the "most interesting" to study? Professor Ashley Villar at the Center for Astrophysics | Harvard & Smithsonian has made her career out of developing machine learning techniques to answer this very question.

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