PIRSA:22050010

Machine Learning (2021/2022)

Carrasquilla Álvarez, J.F. (2022). Machine Learning (2021/2022). Perimeter Institute. https://pirsa.org/22050010

Carrasquilla Álvarez, Juan Felipe. Machine Learning (2021/2022). Perimeter Institute, May. 03, 2022, https://pirsa.org/22050010 

          @misc{ pirsa_PIRSA:22050010,
            doi = {},
            url = {https://pirsa.org/22050010},
            author = {Carrasquilla {\'A}lvarez, Juan Felipe},
            keywords = {},
            language = {en},
            title = {Machine Learning (2021/2022)},
            publisher = {Perimeter Institute},
            year = {2022},
            month = {may},
            note = {PIRSA:22050010 see, \url{https://pirsa.org}}
          }

Juan Carrasquilla ETH Zurich

Collection
Talk Type Course

Abstract

This course is designed to introduce modern machine learning techniques for studying classical and quantum many-body problems encountered in condensed matter, quantum information, and related fields of physics. Lectures will focus on introducing machine learning algorithms and discussing how they can be applied to solve problem in statistical physics. Tutorials and homework assignments will concentrate on developing programming skills to study the problems presented in lecture.