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DTSTAMP:20260614T184623Z
UID:7f7c1435-35a5-4f1b-8226-dddc3587708d
DTSTART:20210616T090000Z
DTEND:20210617T163000Z
DESCRIPTION:With the rise in high-throughput sequencing technologies\, the 
 volume of omics data has grown exponentially in recent times and a major i
 ssue is to mine useful knowledge from these data which are also heterogene
 ous in nature. Machine learning (ML) is a discipline in which computers pe
 rform automated learning without being programmed explicitly and assist hu
 mans to make sense of large and complex data sets. The analysis of complex
  high-volume data is not trivial and classical tools cannot be used to exp
 lore their full potential. Machine learning can thus be very useful in min
 ing large omics datasets to uncover new insights that can advance the fiel
 d of bioinformatics.\n\nThis 2-day course will introduce participants to t
 he machine learning taxonomy and the applications of common machine learni
 ng algorithms to omics data. The course will cover the common methods bein
 g used to analyse different omics data sets by providing a practical conte
 xt through the use of basic but widely used R libraries. The course will c
 omprise a number of hands-on exercises and challenges where the participan
 ts will acquire a first understanding of the standard ML processes\, as we
 ll as the practical skills in applying them on familiar problems and publi
 cly available real-world data sets.
SUMMARY:Introduction to Machine Learning using R
URL;VALUE=URI:https://fpsom.github.io/2021-06-ml-elixir-fr/
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