BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//CERN//INDICO//EN
BEGIN:VEVENT
SUMMARY:Reproducible Machine Learning Workflows for Scientists Workshop 20
 25
DTSTART:20250812T133000Z
DTEND:20250814T210000Z
DTSTAMP:20260721T131200Z
UID:indico-event-14982@indico.global
CONTACT:matthew.feickert@wisc.edu
DESCRIPTION:Speakers: Matthew Feickert (University of Wisconsin Madison (U
 S))\, Ryan Bemowski (University of Wisconsin-Madison)\, Christopher Endema
 nn (University of Wisconsin-Madison)\, Raheem Hashmani (Data Science Insti
 tute)\n\nNational Workshop\nScientific researchers need reproducible softw
 are environments for complex applications that can run across heterogeneou
 s computing platforms. Modern open source tools\, like Pixi\, provide auto
 matic reproducibility solutions for all dependencies while providing a hig
 h level interface well suited for researchers.\nThis in-person workshop wi
 ll provide a practical introduction to using Pixi to easily create computi
 ng environments for scientific and AI/ML workflows that benefit from hardw
 are acceleration\, across multiple machines and platforms. The focus will 
 be on applications using Python machine learning libraries with CUDA enabl
 ed\, as well as deploying these environments to production settings in Lin
 ux container images. This workshop will not teach machine learning concep
 ts\, but will focus on the methodologies and tools to make existing machin
 e learning workflows reproducible.The afternoon sessions of the workshop w
 ill focus on applying the morning lesson content to real applications\, an
 d so participants are strongly encouraged to bring a research project (or 
 idea) with them to the workshop to apply what they learn.Registration is c
 urrently FULL. If participants are unable to attend their registration slo
 ts will be made available again\, so check back in the next week.\nPartici
 pant Information\nNo prior experience with these tools and technologies is
  expected to participate in the workshop\, though if you do have experienc
 e that is great. Participants who do not have experience with machine lear
 ning but have interest in general hardware acceleration for computing are 
 encouraged to register for the workshop also (the workshop focuses on enab
 ling reproduction for existing hardware accelerated workflows\, not machin
 e learning techniques).Basic experience with:\n\nfile systems\nversion con
 trol with Git\nand programming in Python (or a similar language)\n\nis exp
 ected.The workshop is free and there are no fees associated with it. To pa
 rticipate please apply to register for the workshop.\nWho should apply to
  participate in this workshop?\nThe target audience the workshop material 
 was designed for is "early career researchers" but that should be broadly 
 interpreted. All career stages (from students to faculty and staff) are we
 lcome to apply and participate!\nParticipant requirements\nParticipants wi
 ll need to have the following things to participate in the workshop\n\nA l
 aptop \n\nWe will be using the command line so you will need a terminal e
 mulator program installed (e.g. Terminal\, Ghostty\, Windows Terminal). Yo
 ur operating system's default one is fine.\nYou will be installing softwar
 e onto your machine so you will need some free disk space as well\nYou wil
 l be writing some configuration files and code so you will also need a tex
 t editor program (e.g. VS Code\, Vim\, Emacs) that you know how to use ins
 talled\nIf you are using Windows\, it is strongly recommended that you use
  the Windows Subsystem for Linux (WSL 2) and Windows Terminal.\n\n\nA pers
 onal GitHub account\n\nIt doesn't need to be GitHub (GitLab.com or some ot
 her alternative would be fine too) but for the sake of consistency of inst
 ruction GitHub is preferred.\n\n\n\nLimited lodging stipend\nRegistration 
 for the workshop is free\, and for a limited number of (non-local to Madi
 son) participants\, three (3) nights of lodging at the workshop hotel will
  be covered in a lodging stipend. To be eligible for the lodging stipend y
 ou must apply for it during registration. Decisions on lodging stipends wi
 ll be determined by Friday\, July 18th (2025-07-18) at the latest.\nWorksh
 op resources and references\nMaterials and resources\n\nWorkshop materials
  website\nData Science Hub Slack sign up Google Doc\n\nReferences\nIf part
 icipants feel they would benefit from review of some of the foundational m
 aterial of the workshop they might consider the following lessons from The
  Carpentries\n\nThe Unix Shell\nVersion control with Git\nProgramming with
  Python\n\nWhile no machine learning or deep learning background is assume
 d for this workshop\, participants may also wish to explore these Carpentr
 ies resources in the future:\n\nIntroduction to Machine Learning with scik
 it-learn\nIntroduction to Deep Learning\nIntroduction to Natural Language 
 Processing / Text Analysis\nTrustworthy AI: Validity\, Fairness\, Explaina
 bility\, and Uncertainty Assessments\n\nInstructor team\n\nMatthew Feicker
 t (UW--Madison\, Data Science Institute)\nChris Endemann (UW--Madison\, Da
 ta Science Hub)\nRyan Bemowski (UW--Madison\, Data Science Hub)\nRaheem Ha
 shmani (UW--Madison\, Data Science Institute)\n\nAcknowledgements\nThis wo
 rkshop is supported by the US Research Software Sustainability Institute (
 URSSI) via grant G-2022-19347 from the Sloan Foundation.The workshop used 
 services provided by the Open Science Grid Consortium [1\,2\,3\,4]\, which
  is supported by the National Science Foundation awards #2030508 and #2323
 298.The University of Wisconsin-Madison Data Science Institute provided ad
 ditional support.NVIDIA provided cloud GPU resources on the Brev platform.
 \n\n\n\n\n\n\n\n\n\n\n \n\nhttps://indico.global/event/14982/
LOCATION:Orchard View Room (Discovery Building)
URL:https://indico.global/event/14982/
END:VEVENT
END:VCALENDAR