PHYS 243: Foundations of Applied Machine Learning
Machine learning (ML) has emerged as a very powerful tool in Data Science. With ML techniques, computational systems can adaptively improve their performances using experimental data to train. This allows construction of algorithms that can learn from and make predictions based on data. Machine learning is a demanding discipline and is presently used to extract information from data in a variety of fields. This course is designed to prepare students to work in the Data Science disciplines using ML techniques, introduce existing ML techniques and algorithms. The course will provide practical experience and case studies based on real data. It covers examples from different disciplines- physics, astronomy, biology, neuroscience, finance. The course also provides an introduction to deep learning and its applications. By the successful completion of this course students would be able to define solutions for problems in a variety of disciplines using ML or deep learning techniques.