Machine Learning for a Rainy Day
Machine Learning for a Rainy Day by Sergey Kirshner - Machine Learning Summer School at Purdue, 2011. Given its importance in our everyday lives, the use of machine learning in atmospheric sciences up to recently has been dramatically underutilized. However, in part due to the explosion in atmospheric data measurements, climate science is receiving increasing attention from statisticians and machine learning researchers. In this talk, I will survey potential applications of machine learning to atmospheric sciences while highlighting three specific problems related to modeling of rainfall: modeling of multi-site daily rainfall time series, characterizing droughts, and improving prediction of severe weather.
|Machine Learning for a Rainy Day
Machine Learning Summer School at Purdue, 2011