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SUMMARY:[Workshop] Julia for High Performance Data Analysis
DTSTART:20260526T070000Z
DTEND:20260529T100000Z
DTSTAMP:20260501T122300Z
UID:indico-event-480@events.hpc-portal.eu
DESCRIPTION:Overview\nJulia is a modern high-level programming language th
 at is fast (on par with traditional HPC languages like Fortran and C) and 
 relatively easy to write like Python or Matlab. It thus solves the two-lan
 guage problem\, i.e. when prototype code in a high-level language needs to
  be combined with or rewritten in a lower-level language to improve perfor
 mance. Although Julia is a general-purpose language\, many of its features
  are particularly useful for numerical scientific computation\, and a wide
  range of both domain-specific and general libraries are available for sta
 tistics\, machine learning\, and numerical modeling.\nJoin us for Julia fo
 r High Performance Data Analysis\, a hands-on workshop designed to equip y
 ou with practical skills for working with large datasets\, optimizing code
 \, and leveraging Julia’s rich ecosystem of libraries. You’ll explore 
 real-world applications in data analysis\, numerical computation\, and mac
 hine learning\, all while discovering how Julia can streamline your workfl
 ow and elevate your performance without sacrificing code readability.\nWho
  is this workshop for?\nThis workshop is aimed at students\, researchers\,
  and developers who:\n\nAre already familiar with one or more programming 
 languages such as Julia\, Python\, R\, C/C++\, Fortran\, or Matlab.\nWork 
 with large datasets or need to perform computationally intensive modeling 
 and analysis.\nWant to develop high-performance data science applications 
 while staying within a productive\, high-level programming environment.\n\
 nPrerequisites\n\nExperience with one or more programming languages.\nFami
 liarity with basic concepts in linear algebra and machine learning.\nBasic
  experience working in a terminal is helpful.\n\nKey takeaways\nThis onlin
 e workshop will start by briefly covering the basics of Julia’s syntax a
 nd features\, and then introduce methods and libraries which are useful fo
 r writing high-performance code for modern HPC systems. After attending th
 e workshop\, you will:\n\nBe comfortable with Julia’s syntax\, built-in 
 package manager\, and development tools.\nUnderstand core language feature
 s like its type system\, multiple dispatch\, and composability.\nBe able t
 o write your own Julia packages from scratch.\nKnow how to perform various
  linear algebra analysis on datasets.\nBe productive in analyzing and visu
 alizing large datasets in Julia using dataframes and visualization package
 s.\nBe familiar with several Julia libraries for visualization and machine
  learning.\nUnderstand how to analyze large datasets efficiently in Julia 
 using statistical methods.\n\nTentative Agenda\n\n\n\nTime (9:00-12:00) (C
 ET)\nContents\n\n\n\n\nMay 26\nMotivation\, julia syntax\, special Julia f
 eatures\, developing in Julia\, package ecosystem\n\n\nMay 27\nMotivation 
 (julia for data analysis)\, data formats and dataframes\, linear algebra\,
  machine learning (data part)\n\n\nMay 28\nMachine learning\, clustering a
 nd classification\, deep learning\n\n\nMay 29\nNon-linear regression\, sci
 entific machine learning\, conclusions and outlook\n\n\n\nRegulations\nDue
  to EuroCC2 regulations\, we CAN NOT ACCEPT generic or private email addre
 sses. Please use your official university or company email address for reg
 istration.\nThis training is intended for users established in the Europea
 n Union or a country associated with Horizon 2020. You can read more about
  the countries associated with Horizon2020 HERE.\nContact\nFor questions r
 egarding this workshop or general questions about ENCCS training events\, 
 please contact training@enccs.se.\n\nhttps://events.hpc-portal.eu/event/48
 0/
LOCATION:Online
URL:https://events.hpc-portal.eu/event/480/
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