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SUMMARY:Amyloid Workshop: User-friendly analysis of spectroscopy data with
  Quasar - multivariate statistics and machine learning
DTSTART;VALUE=DATE-TIME:20210113T130000Z
DTEND;VALUE=DATE-TIME:20210115T170000Z
DTSTAMP;VALUE=DATE-TIME:20260527T212005Z
UID:indico-event-165@lindico453.srv.lu.se
DESCRIPTION:\n\nWelcome to the Amyloid workshop: User-friendly analysis of
  spectroscopy data with Quasar - multivariate statistics and machine learn
 ing.\n\nLINXS\, in collaboration with the SMIS beamline at SOLEIL and the
  Biolab from the University of Ljubljana\, is organising a 3-half day han
 ds-on workshop to introduce the QUASAR software\, to address the infrared 
 user community's need for a user-friendly and open-source software for dat
 a analysis\n\nThis 3-half day hands-on training will be fully digital duri
 ng January 13-15\, 2021.  Participants will be selected on a fair distri
 bution basis across the research groups and giving priority to early caree
 r.\n\nDuring this workshop\, we will focus on spectroscopic data analysis.
  The workshop is targeted at hyper-spectral imaging users (current\, futur
 e or potential) working on biomedical applications\, material-engineering\
 , physical-chemical sciences\, and more. The purpose of this training is t
 o provide a practical introduction to the QUASAR software\, using tutoria
 ls and examples on synchrotron data sets as well as real-life Raman and IR
  imaging datasets.\n\nWhat is QUASAR?\n\nQUASAR is an open-source softwar
 e for hyper-spectral imaging techniques (based on the Orange machine learn
 ing and data visualization suite).\nQUASAR allows user-friendly analysis 
 using visual programming. Routine tools like baseline correction\, normali
 zation\, different versions of EMSC\, differentiation and smoothing can be
  combined with multivariate statistical and machine learning methods\, suc
 h as principal component analysis or various clustering methods. Savable a
 nd shareable workflows ensure consistent analysis across different project
 s\, or the development of different analysis to same large dataset. Visual
 ization tools enable quick inspection of the data and the results of the a
 nalyses.\nThe goal of the workshop is to teach the basic operations of che
 mical imaging to prepare the student to generate and interpret such images
  using QUASAR\, new free software.\n\nWhy should you attend?\n\nThe worksh
 op will bring together curious students and young researchers and introduc
 e them to essential data mining and machine learning concepts in spectrosc
 opic data analysis. Participant will learn about data visualization and ma
 chine learning with Quasar. Upon completion\, participants will be able to
  analyze your own data and use them to develop predictive models. The work
 shop will be hands-on\, with examples or own data\n\n Workshop content\n
 \n·Data exploration and visualization.\n·Clustering\, uncovering of grou
 ps in data.\n·Classification and predictive modeling.\n\nINCLUDED\n\n·3-
 day theory/hands-on course on key approaches of data science\n·Free softw
 are and data sets used during the course\n·Certificate of attendance\n\nA
 pplication\n\nApplications are now open\, and will be closed 10th of Janua
 ry 2021.\nThe workshop is limited to max 20 people selected on a fair dis
 tribution basis across the research groups\, giving priority to early care
 er scientists.\n\nFee\n\nThere is no fee for digital participation.\n\nLec
 turers\n\nDr. Ferenc Borondics\, SOLEIL\, France\nDr. Christophe Sandt\,
  SOLEIL\, France\nDr. Marko Toplak\, University of Ljubljana\,  Slove
 nia\n\nOrganizers\n\nThe Amyloid working group at LINXS and AI Lund (websi
 te)\n\nWorkshop agenda\n\nDay 1\, January 13\, 2- 6 pm\nGetting started wi
 th Quasar (installation\, basic Orange and Quasar functionality)\nSpectral
  Preprocessing\nAdvanced visualization\nStatistical inspection of data\nPC
 A\, PCA imaging\nHands-on work with participants' data\n\n Day 2\, Januar
 y 14\, 2- 6 pm\nSupervised learning\nIntroduction to supervised learning\n
 Classification of spectra and hyperspectral datasets using various method
 s\nModel inspection and cross-validation\nCommon errors\nHands-on work wit
 h participants' data\n\nDay 3\, January 15\, 2- 6 pm\nUnsupervised learnin
 g\nIntroduction to unsupervised learning\nClustering of spectra and hypers
 pectral datasets using various methods\nCommon errors\nPartial Least Squar
 es regressionxx\nHands-on work with participants' data\n\n\n\n\nhttps://li
 ndico453.srv.lu.se/event/165/
LOCATION:On Zoom
URL:https://lindico453.srv.lu.se/event/165/
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