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TZID:Asia/Riyadh
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DTSTART:20380119T061407
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BEGIN:VEVENT
DTSTAMP:20250330T101932Z
UID:2D265D75-7389-456C-876E-55396FC39265
DTSTART;TZID=Asia/Riyadh:20250428T200000
DTEND;TZID=Asia/Riyadh:20250428T213000
DESCRIPTION:Workshop Series Introduction\n\nThis workshop is one of a serie
 s of workshops that aim to enhance understanding of data modeling processe
 s for those interested in artificial intelligence and machine learning. Sp
 ecifically\, it is designed to prepare participants for the first edition 
 of the upcoming [IEEEModelthon 1.0](https://events.vtools.ieee.org/m/44393
 8) on [Kaggle](https://www.kaggle.com/).\n\nWorkshop Overview\n\nIn this w
 orkshop\, you will explore various data modeling tasks and learn about dif
 ferent types of machine learning algorithms. In addition\, you will be int
 roduced to key data modeling concepts and the most common challenges encou
 ntered in the learning process and how to fine-tune your model&#39;s performan
 ce.\n\nPurpose\n\nPrimarily\, this workshop covers methods for training ma
 chine learning models using the sklearn library\, based on the pre-prepare
 d data from the previous step\, and how to check their performance and adj
 ust their parameters\, if needed\, using one of the optimization algorithm
 s!\n\nObjective and Outcome\n\nThis workshop is essential for anyone in a 
 data-driven field. Mainly\, the outcome of this phase is a list of 3 to 5 
 promising models and integrating them in one amazing ensemble model!\n\nFo
 r more information about the IEEEModelthon1.0\, click [here](https://event
 s.vtools.ieee.org/m/443938).\n\nVirtual: https://events.vtools.ieee.org/m/
 445224
LOCATION:Virtual: https://events.vtools.ieee.org/m/445224
ORGANIZER:ieee.computersociety.aabu@gmail.com
SEQUENCE:91
SUMMARY:Machine Learning Essentials: Model Training &amp; Optimization
URL;VALUE=URI:https://events.vtools.ieee.org/m/445224
X-ALT-DESC:Description: &lt;br /&gt;&lt;h3&gt;&lt;strong&gt;Workshop Series Introduction&lt;br&gt;&lt;
 /strong&gt;&lt;/h3&gt;\n&lt;p&gt;This workshop is one of a series of workshops that aim t
 o enhance understanding of data modeling processes for those interested in
  artificial intelligence and machine learning. Specifically\, it is design
 ed to prepare participants for the first edition of the upcoming &lt;a title=
 &quot;IEEEModelthon 1.0&quot; href=&quot;https://events.vtools.ieee.org/m/443938&quot; target=
 &quot;_blank&quot; rel=&quot;noopener&quot;&gt;&lt;em&gt;&lt;strong&gt;IEEEModelthon 1.0&lt;/strong&gt;&lt;/em&gt;&lt;/a&gt; on
  &lt;em&gt;&lt;a title=&quot;Kaggle&quot; href=&quot;https://www.kaggle.com/&quot; target=&quot;_blank&quot; rel=
 &quot;noopener&quot;&gt;&lt;strong&gt;Kaggle&lt;/strong&gt;&lt;/a&gt;&lt;/em&gt;.&lt;/p&gt;\n&lt;h3&gt;&lt;br&gt;&lt;strong&gt;Workshop
  Overview&lt;/strong&gt;&lt;/h3&gt;\n&lt;p&gt;In this workshop\, you will explore various da
 ta modeling tasks and learn about different types of &lt;strong&gt;machine learn
 ing algorithms&lt;/strong&gt;. In addition\, you will be introduced to key data 
 modeling concepts and the most common challenges encountered in the learni
 ng process and how to fine-tune your model&#39;s performance.&lt;/p&gt;\n&lt;h3&gt;&lt;br&gt;&lt;st
 rong&gt;Purpose&lt;/strong&gt;&lt;/h3&gt;\n&lt;p&gt;Primarily\, this workshop covers methods fo
 r training machine learning models using the &lt;strong&gt;sklearn&lt;/strong&gt; libr
 ary\, based on the &lt;strong&gt;pre-prepared&lt;/strong&gt; &lt;strong&gt;data&lt;/strong&gt; fro
 m the previous step\, and how to check their performance and adjust their 
 parameters\, if needed\, using one of the optimization algorithms!&lt;/p&gt;\n&lt;h
 3&gt;&lt;strong&gt;&lt;br&gt;Objective and Outcome&lt;/strong&gt;&lt;/h3&gt;\n&lt;p&gt;This workshop is ess
 ential for anyone in a data-driven field. Mainly\, the outcome of this pha
 se is a list of 3 to 5 promising models and integrating them in one amazin
 g ensemble model!&lt;br&gt;&lt;br&gt;&lt;br&gt;For more information about the&amp;nbsp\;&lt;strong&gt;
 IEEEModelthon1.0&lt;/strong&gt;\, click &lt;a title=&quot;IEEEModelthon1.0&quot; href=&quot;https:
 //events.vtools.ieee.org/m/443938&quot; target=&quot;_blank&quot; rel=&quot;noopener&quot;&gt;here&lt;/a&gt;
 .&lt;/p&gt;
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