+DS IPLE: The Impact of Machine Learning in Astrophysics and Cosmology
There is a big data revolution happening in astrophysics as the next generation of telescopes are coming online, with 20 terabytes of data coming from a single telescope per night. From this large amount of data, scientists are trying to find subtle clues that can help uncover the most profound mysteries in the universe. Here, I will focus on some of the machine learning and deep learning techniques that have been employed to classify different types of stars, galaxies and transients. I will go over recent successes and challenges, and show off the work I do, demonstrated by one of the latest and most popular Kaggle machine-learning competitions ever called 'PLAsTiCC Astronomical Classification: Can you help make sense of the Universe?' This session is part of the Duke+Data Science (+DS) program in-person learning experiences (IPLEs). To learn more, please visit https://plus.datascience.duke.edu/