PIRSA:22040064

Machine Learning (2021/2022)

APA

Hayward, L. (2022). Machine Learning (2021/2022). Perimeter Institute for Theoretical Physics. https://pirsa.org/22040064

MLA

Hayward, Lauren. Machine Learning (2021/2022). Perimeter Institute for Theoretical Physics, Apr. 04, 2022, https://pirsa.org/22040064

BibTex

          @misc{ scivideos_PIRSA:22040064,
            doi = {},
            url = {https://pirsa.org/22040064},
            author = {Hayward, Lauren},
            keywords = {},
            language = {en},
            title = {Machine Learning (2021/2022)},
            publisher = {Perimeter Institute for Theoretical Physics},
            year = {2022},
            month = {apr},
            note = {PIRSA:22040064 see, \url{https://scivideos.org/index.php/pirsa/22040064}}
          }
          

Lauren Hayward Perimeter Institute for Theoretical Physics

Talk numberPIRSA:22040064
Source RepositoryPIRSA
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.