BEGIN:VCALENDAR
VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:Asia/Kolkata
BEGIN:STANDARD
DTSTART:19451014T230000
TZOFFSETFROM:+0630
TZOFFSETTO:+0530
TZNAME:IST
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20200924T114339Z
UID:5407174C-9551-4373-9919-54CCAE414E6C
DTSTART;TZID=Asia/Kolkata:20200701T140000
DTEND;TZID=Asia/Kolkata:20200701T160000
DESCRIPTION:The speaker has started the discussion with the introduction of
  the topic\, Machine Learning\, and explained different Machine Learning a
 lgorithms.\n Then\, the topic-” UnSupervised Learning” was explaine
 d saying that it was a method dealt with the data without any specific lab
 els.\n Major clustering approaches like the Partitioning approach\, Hie
 rarchical approach\, and Density-based approach were discussed and methods
  to implement those approaches were also stated.\n Different Clustering
  Applications in the practical scenario were also discussed and this kind 
 of practical approach seems very interesting to the\nparticipants.\n\nSpea
 ker(s): Dr. Y. Padma Sai\, \n\nAgenda: \nThe lecture was aimed at making t
 he participants understand the method of Unsupervised learning which invol
 ves the process of clustering. With the idea of this clustering\, one can 
 detect the patterns of data without any labels.\n\nHyderabad\, Andhra Prad
 esh\, India\, Virtual: https://events.vtools.ieee.org/m/240904
LOCATION:Hyderabad\, Andhra Pradesh\, India\, Virtual: https://events.vtool
 s.ieee.org/m/240904
ORGANIZER:Rajeshwari_I@ieee.org
SEQUENCE:1
SUMMARY:ML Webinar Series (6)- Clustering
URL;VALUE=URI:https://events.vtools.ieee.org/m/240904
X-ALT-DESC:Description: &lt;br /&gt;&lt;p&gt;The speaker has started the discussion wit
 h the introduction of the topic\, Machine Learning\, and explained differe
 nt Machine Learning algorithms.&lt;br /&gt; Then\, the topic-&amp;rdquo\; UnSuper
 vised Learning&amp;rdquo\; was explained saying that it was a method dealt wit
 h the data without any specific labels.&lt;br /&gt; Major clustering approach
 es like the Partitioning approach\, Hierarchical approach\, and Density-ba
 sed approach were discussed and methods to implement those approaches were
  also stated.&lt;br /&gt; Different Clustering Applications in the practical 
 scenario were also discussed and this kind of practical approach seems ver
 y interesting to the&lt;br /&gt;participants.&lt;/p&gt;&lt;br /&gt;&lt;br /&gt;Agenda: &lt;br /&gt;&lt;p&gt;Th
 e lecture was aimed at making the participants understand the method of Un
 supervised learning which involves the process of clustering. With the ide
 a of this clustering\, one can detect the patterns of data without any lab
 els.&lt;/p&gt;
END:VEVENT
END:VCALENDAR