In this post, Metis Sr. Data Scientist Roberto Reif explores transfer learning, a method of using a deep learning model that has already been trained to solve one problem containing large amounts of data, and applying it (with some minor modifications) to solve a different problem that contains small amounts of data. He analyzes the limit for how small a data set needs to be in order to successfully apply this technique.
By Roberto Reif • May 24, 2018
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