Abstract: Traditional machine-learning approaches face limitations when confronted with insufficient data. Transfer learning addresses this by leveraging knowledge from closely related domains. The ...
This workshop is built for researchers and graduate students who want to understand their data before modeling. Participants learn how to use R and the tidyverse to explore patterns, summarize key ...
Abstract: Causality as a phenomenon still seems to be an old and open issue as the philosophy itself. Discovering such relationships among data, in most of cases results in unsuccessfully effort.
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