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DTSTAMP:20250804T200052Z
DESCRIPTION: \n\n \n\n \n\n \n\n \n\n \n\nDescription:\n	\n	Modern -omics dat
 asets are very highly dimensional\, covering samples (cells\, people\, bac
 teria\, etc) across thousands to millions of variables (SNPs\, genes\, pro
 teins\, etc). Participants will learn about methods like PCA\, MDS\, t-SNE
 \, and UMAP\, and their applications in investigating data that lives in h
 igh dimensions.\n\nWe will cover the motivations and ideas behind the meth
 ods and go over examples using both artificial and real-world data. By the
  end of the session\, you will be able to code implementations of dimensio
 n reduction as well as visualize your data in useful ways and consider app
 roaches for downstream analysis.\n\nWorkshop pre-assesment\n\nThe methods 
 covered have implementations in Python and R\, and the course will be taug
 ht using Python notebooks (with some equivalent code in R provided).\n\nTh
 ere will be some linear algebra\, analysis\, and statistics -- knowledge o
 f these topics will be useful for but not critical to participation.\n\nIn
 structor: Alex Diaz-Papkovich\n	\n	Fee: $25 (seating is limited)\n	*Reimburse
 ment is available to ºÚÁϲ»´òìÈ students after attending the workshop.\n\n \n
 \nTo Register: via Eventbrite\n\nFor more information on workshops email u
 s at: workshop-micm [at] mcgill.ca (subject: Workshop) \n
DTSTART:20200625T170000Z
DTEND:20200625T210000Z
SUMMARY:Dimension reduction methods
URL:/micm/channels/event/dimension-reduction-methods-3
 20449
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