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VERSION:2.0
PRODID:icalendar-ruby
CALSCALE:GREGORIAN
BEGIN:VEVENT
DTSTAMP:20260710T121147Z
UID:4719fe65-f04d-43e3-a1ae-b6f7c731e2f3
DTSTART:20251125T093000Z
DTEND:20251127T173000Z
DESCRIPTION:This course on unsupervised learning provides a systematic intr
 oduction to dimensionality reduction and clustering techniques. The course
  covers fundamental concepts of unsupervised learning and data normalizati
 on\, then progresses through the practical applications of Principal Compo
 nent Analysis (PCA)\, t-Distributed Stochastic Neighbor Embedding (t-SNE)\
 , and hierarchical clustering algorithms. \n\nThe course emphasizes both t
 heoretical understanding and hands-on application\, teaching students to r
 ecognize when different techniques are appropriate and when they may fail.
  A key learning objective is understanding the limitations of linear metho
 ds like PCA. Students learn to evaluate the performance of unsupervised le
 arning methods across diverse data types\, with the ultimate goal of gener
 ating meaningful hypotheses for further research.\n\n\n\nIf you do not hav
 e a University of Cambridge [Raven account](https://legacy.raven.cam.ac.uk
 /auth/account/) please book or register your interest [here](http://bioinf
 otraining.bio.cam.ac.uk/booking-form/?event-id=5889959&amp\;course-title=A
 pplied%20Unsupervised%20Machine%20Learning%20in-person).\nIf for any reaso
 n the above links do not work\, please email [Research Informatics Trainin
 g Team](https://training.cam.ac.uk/bioinformatics/info/contact) with detai
 ls of your course enquiry.\n\nAdditional information\n\n* Our courses are 
 only free for registered University of Cambridge students. All other parti
 cipants will be charged according to our  [charging policy](http://www.tra
 ining.cam.ac.uk/bioinformatics/info/charging).\n* Attendance will be taken
  on all courses and a charge is applied for non-attendance. After you have
  booked a place\, if you are unable to attend any of the live sessions\, p
 lease email the [Research Informatics Training Team](https://training.cam.
 ac.uk/bioinformatics/info/contact).\n* Further details regarding eligibili
 ty criteria are available [here](http://www.training.cam.ac.uk/bioinformat
 ics/info/eligibility).
LOCATION:Craik-Marshall Building
SUMMARY:Applied Unsupervised Machine Learning (IN-PERSON)
URL;VALUE=URI:http://training.csx.cam.ac.uk/bioinformatics/event/5889959
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