Date: March 29, 2018

Speaker: Dr. Viviana Acquaviva (NYCCT)

Title: The science of machine learning

Abstract: Machine learning is the discipline of teaching computers to recognize, classify and predict relationships within data. It has countless applications in the most diverse fields: it can be used to generate to recommend movies and articles, to generate poems in the style of Shakespeare, to accelerate diagnoses of dangerous diseases, to prevent insurance fraud, to improve system security, and many other endeavors. At their core though, machine learning algorithms are just a set of clever mathematical tools that allow us to re-map complicated questions onto simpler optimization problems. We discuss our ID course, Machine Learning for Physics and Astronomy, in which we use data sets from Physics and Astronomy and Python programming to learn machine learning from the ground up. We present a selection of algorithms to solve challenges such as discovering new elementary particles, finding dark energy, identifying variable stars, and understanding the origin of galaxy shapes.