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SUMMARY:HSF/IRIS-HEP Machine Learning Training - Intermediate Level  (Virt
 ual)
DTSTART:20260803T123000Z
DTEND:20260804T165000Z
DTSTAMP:20260805T202500Z
UID:indico-event-1706524@indico.cern.ch
CONTACT:hsf-training-ml-aug26-organizers@googlegroups.com
DESCRIPTION:Speakers: Richa Sharma (University of Puerto Rico (US))\, Vale
 riia Lukashenko (University of Zurich (CH))\, Alexander Moreno Briceño (U
 niversidad Antonio Nariño)\, Andres Rios-Tascon (Princeton University)\n\
 n      \nWe are very excited to announce a training event on Machine Le
 arning/Deep Learning organised through the HEP Software Foundation and IRI
 S-HEP \n \nAll sessions will take place in the US Eastern Time zone.\nPl
 ease contact the organizers (email us) in case of any questions.\nWhat exa
 ctly will I learn?\nThe main objective of this course are\n\n\nTo introduc
 e you to the basics of Machine learning with examples.\n\n\nTo develop a s
 ense of statistics/data science algorithms that goes under the hood of a M
 L model.\n\n\nExplain the terminology of machine learning.\n\n\nIntroducin
 g you to some Python frameworks to start building your first Machine.\n\n\
 nGetting familiarize with basic ML models that are although very common bu
 t can serve as a basic starting point.\n\n\nGetting you prepared to learn 
 on your own once this course is over.\n\n\nAre there any prerequisites?\nY
 es! \nHard Prerequisites\nParticipants should have basic experience with 
 Python\, including writing or modifying simple scripts\, using functions a
 nd packages\, and understanding simple error messages. You should also be 
 able to run and edit a Jupyter Notebook or Google Colab notebook\, use bas
 ic terminal commands\, and install Python packages when needed. A working 
 Python environment is required\; Google Colab will be supported\, although
  a local conda\, mamba\, or pip environment is encouraged for the exercise
 s.\nSoft Prerequisites\nBasic familiarity with functions\, vectors and mat
 rices\, derivatives\, probability\, and statistics will be helpful. Prior 
 experience with NumPy\, Pandas\, plotting\, Scikit-Learn\, PyTorch\, Git\,
  machine learning\, or HEP data analysis is useful but not required. The c
 ourse is intended for participants with different levels of ML experience\
 , but it will not provide an introduction to Python programming.\nWho is s
 upporting this?\nThis event is supported by CERN and U.S. National Science
  Foundation Cooperative Agreement PHY-2323298 (IRIS-HEP).\nWho is teaching
  this thing?\nThis is a hands-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 filling these roles are listed below.  \nInstructor
 s: \n\n\n\nArghya Chattopadhyay (University of Puerto Rico Mayaguez)\n\n\
 n\nMentors (on Slack): \n\nQuinn Campagna (University of Mississippi)\nMa
 teo E Lisondo (University of Puerto Rico Mayaguez)\nKaran Singh \nAashirv
 ad (Manipal Academy of Higher Education)\nJuvenal Bassa (University of Pue
 rto Rico Mayaguez)\n\n\nhttps://indico.cern.ch/event/1706524/
LOCATION:Virtual
URL:https://indico.cern.ch/event/1706524/
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