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VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:Asia/Colombo
BEGIN:DAYLIGHT
DTSTART:20380119T084407
TZOFFSETFROM:+0530
TZOFFSETTO:+0530
RRULE:FREQ=YEARLY;BYDAY=3TU;BYMONTH=1
TZNAME:+0530
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BEGIN:STANDARD
DTSTART:20060415T000000
TZOFFSETFROM:+0600
TZOFFSETTO:+0530
RRULE:FREQ=YEARLY;BYDAY=3SA;BYMONTH=4
TZNAME:+0530
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BEGIN:VEVENT
DTSTAMP:20250130T075946Z
UID:1BF3A87D-25E5-46D7-BFD9-8398CF2A03D9
DTSTART;TZID=Asia/Colombo:20240613T180000
DTEND;TZID=Asia/Colombo:20240913T190000
DESCRIPTION:[]\n\nThe Workshop 1 covered essential techniques like data cle
 aning\, where you learned to handle missing or inconsistent data\, ensurin
 g datasets are reliable for analysis. Feature selection was also explored\
 , teaching you how to identify the most relevant variables for your models
  to improve efficiency and accuracy. Additionally\, data preprocessing tec
 hniques were discussed to help prepare raw data for machine learning algor
 ithms. The workshop also introduced the Kaggle platform\, a popular online
  community for data scientists to practice\, compete\, and collaborate on 
 various data science projects.\n\nSpeaker(s): Mahesha Viduranga\, \n\nVirt
 ual: https://events.vtools.ieee.org/m/436615
LOCATION:Virtual: https://events.vtools.ieee.org/m/436615
ORGANIZER:ieeepdn@gmail.com
SEQUENCE:7
SUMMARY:Predicta 1.0 - Workshop 1
URL;VALUE=URI:https://events.vtools.ieee.org/m/436615
X-ALT-DESC:Description: &lt;br /&gt;&lt;p&gt;&lt;img style=&quot;display: block\; margin-left: 
 auto\; margin-right: auto\;&quot; src=&quot;https://events.vtools.ieee.org/vtools_ui
 /media/display/4061b221-35ab-4575-9e64-5b0a28a825a1&quot; alt=&quot;&quot; width=&quot;253&quot; he
 ight=&quot;253&quot;&gt;&lt;/p&gt;\n&lt;p style=&quot;text-align: justify\;&quot;&gt;The &lt;strong&gt;Workshop 1&lt;/
 strong&gt; covered essential techniques like data cleaning\, where you learne
 d to handle missing or inconsistent data\, ensuring datasets are reliable 
 for analysis. Feature selection was also explored\, teaching you how to id
 entify the most relevant variables for your models to improve efficiency a
 nd accuracy. Additionally\, data preprocessing techniques were discussed t
 o help prepare raw data for machine learning algorithms. The workshop also
  introduced the Kaggle platform\, a popular online community for data scie
 ntists to practice\, compete\, and collaborate on various data science pro
 jects.&lt;/p&gt;\n&lt;p&gt;&amp;nbsp\;&lt;/p&gt;
END:VEVENT
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