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BEGIN:VEVENT
SUMMARY:HSF/IRIS-HEP Machine Learning Training - Intermediate Level  (Virt
 ual)
DTSTART;VALUE=DATE:20260802
DTEND;VALUE=DATE:20260804
UID:134041438958
DESCRIPTION:Event from 2026-08-03 12:30:00+00:00 to 2026-08-04 16:50:00+00
 :00\n\nEvent URL: https://indico.cern.ch/event/1706524/\n\nSpeakers: Richa
  Sharma (University of Puerto Rico (US))\, Valeriia Lukashenko (University
  of Zurich (CH))\, Alexander Moreno Briceño (Universidad Antonio Nariño)
 \, Andres Rios-Tascon (Princeton University)\n\n      \nWe are very exc
 ited to announce a training event on Machine Learning/Deep Learning organi
 sed through the HEP Software Foundation and IRIS-HEP \n \nAll sessions w
 ill take place in the US Eastern Time zone.\nPlease contact the organizers
  (email us) in case of any questions.\nWhat exactly will I learn?\nThe mai
 n objective of this course are\n\n\nTo introduce you to the basics of Mach
 ine learning with examples.\n\n\nTo develop a sense of statistics/data sci
 ence algorithms that goes under the hood of a ML model.\n\n\nExplain the t
 erminology of machine learning.\n\n\nIntroducing you to some Python framew
 orks to start building your first Machine.\n\n\nGetting familiarize with b
 asic ML models that are although very common but can serve as a basic star
 ting point.\n\n\nGetting you prepared to learn on your own once this cours
 e is over.\n\n\nAre there any prerequisites?\nYes! \nHard Prerequisites\n
 Participants should have basic experience with Python\, including writing 
 or modifying simple scripts\, using functions and packages\, and understan
 ding simple error messages. You should also be able to run and edit a Jupy
 ter Notebook or Google Colab notebook\, use basic terminal commands\, and 
 install Python packages when needed. A working Python environment is requi
 red\; Google Colab will be supported\, although a local conda\, mamba\, or
  pip environment is encouraged for the exercises.\nSoft Prerequisites\nBas
 ic familiarity with functions\, vectors and matrices\, derivatives\, proba
 bility\, and statistics will be helpful. Prior experience with NumPy\, Pan
 das\, plotting\, Scikit-Learn\, PyTorch\, Git\, machine learning\, or HEP 
 data analysis is useful but not required. The course is intended for parti
 cipants with different levels of ML experience\, but it will not provide a
 n introduction to Python programming.\nWho is supporting this?\nThis event
  is supported by CERN and U.S. National Science Foundation Cooperative Agr
 eement PHY-2323298 (IRIS-HEP).\nWho is teaching this thing?\nThis is a han
 ds-on training and consists of live lectures by the instructors via Zoom.
   Along with this\, there are mentors who will give individual attention 
 and to debug assistance to participants via chat tools.  The people filli
 ng these roles are listed below.  \nInstructors: \n\n\n\nArghya Chattop
 adhyay (University of Puerto Rico Mayaguez)\n\n\n\nMentors (on Slack): \n
 \nQuinn Campagna (University of Mississippi)\nMateo E Lisondo (University 
 of Puerto Rico Mayaguez)\nKaran Singh \nAashirvad (Manipal Academy of Hig
 her Education)\nJuvenal Bassa (University of Puerto Rico Mayaguez)\n\n\nht
 tps://indico.cern.ch/event/1706524/
LOCATION:Virtual
END:VEVENT
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