We have restored access to the website from outside the CERN network, however access from certain worldwide locations is still being blocked (read more here).

CERN Accelerating science

Home > Machine Learning
 
Talk
Title Machine Learning
Video
If you experience any problem watching the video, click the download button below
Download Embed
Mp4:Medium
(800 kbps)		High
(2000 kbps)		More..
Copy-paste this code into your page:
Copy-paste this code into your page to include both slides and lecture:
Author(s) Kagan, Michael Aaron (speaker) (SLAC National Accelerator Laboratory (US))
Corporate author(s) CERN. Geneva
Imprint 2017-04-27. - Streaming video.
Series (Academic Training Lecture Regular Programme ; 2016-2017)
Lecture note on 2017-04-27T11:00:00
Subject category Academic Training Lecture Regular Programme
Abstract Machine learning, which builds on ideas in computer science, statistics, and optimization, focuses on developing algorithms to identify patterns and regularities in data, and using these learned patterns to make predictions on new observations. Boosted by its industrial and commercial applications, the field of machine learning is quickly evolving and expanding. Recent advances have seen great success in the realms of computer vision, natural language processing, and broadly in data science. Many of these techniques have already been applied in particle physics, for instance for particle identification, detector monitoring, and the optimization of computer resources. Modern machine learning approaches, such as deep learning, are only just beginning to be applied to the analysis of High Energy Physics data to approach more and more complex problems. These classes will review the framework behind machine learning and discuss recent developments in the field.
Copyright/License © 2017-2024 CERN
Submitted by maureen.prola-tessaur@cern.ch

 


 Record created 2017-04-27, last modified 2022-11-03
Similar records


External link:
Download fulltext
Event details