DMC Rosalie Tarsala '23: Predicting Galactic Redshift Using Symbolic Regression
Come learn how symbolic regression, mathematical modeling and python comes together when predicting Galactic Redshift with Rosalie Tarsala '23.
Symbolic regression is an emerging tool in data science for the discovery and analysis of relationships in data. It can be used to create a mathematical models of real world phenomena. In this presentation, we will compare and contrast 4 different symbolic regression packages for Python. We will then compare the different results of these packages when predicting the redshift of galaxies based on color measurements. Finally, we will discuss applications of symbolic regression to other types of data science problems. This presentation is based on a project completed as part of La Serena School for Data Science 2022 program.
For any questions, comments, or concerns please contact anation@brynmawr.edu.
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