Learn · CERN

Talk43 min

Reusing ML tools and approaches for HEP data analysis

Andrey USTYUZHANIN · CERN

Watch At CERN

About

In my talk I'm going to give an overview of the ML tools/services Yandex School of Data Analysis (YSDA) team has developed. In particular I will focus on approaches that our team has developed during collaboration with LHCb on HEP data analysis (uGB+FL, GB-reweighting). Each approach is implemented within hep_ml Python package. To get acquainted with this tool you can install it right away in your environment or experiment with it within Reproducible Experiment Platform. I will give initial guidance how you can get started playing with it..

0:00:00 Slide 1

0:00:41 Slide 2

0:01:07 Slide 3

0:02:38 Slide 4

0:03:08 Slide 5

0:03:48 Slide 6

0:04:03 Slide 7

0:04:43 Slide 8

0:05:25 Slide 9

0:07:05 Slide 10

0:08:47 Slide 11

The talk

  1. Reusing ML tools and approaches for HEP data analysis 2015-11-12 · 43 min · CERN's player

Credits and licence

Institution
CERN
Department
LPCC Workshops
Speaker
Andrey USTYUZHANIN
Year
2015
Language
English
Subjects
Computer science
Source
CERN
Licence
CERN, as CERN states it. CERN's terms
Attribution
© CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
Who can watch
CERN gives no rating. Invisible Network shows it to Tweens profiles and older, judged from what the source says about it. How courses are placed