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DTSTART:20210314T030000
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DTSTAMP:20201125T221517Z
UID:56A841BC-1772-4615-8BAC-4CCDA58A12D8
DTSTART;TZID=Canada/Mountain:20201119T180000
DTEND;TZID=Canada/Mountain:20201119T193000
DESCRIPTION:Zoom Link:\n\nhttps://zoom.us/j/92703439681\n\nWorkshop schedul
 e:\n\nIntro to AI [15 min]\n- What is artificial intelligence?\n- What is 
 machine learning? How is it different?\n- What is deep learning? Include a
 n example\n\nBuilding your first neural network [50 min]\n- Hands on exerc
 ise: students will build their first neural network to classify images of 
 clothing (i.e. shirts/pants/jackets etc.).\n- Reflection: What does this t
 each us about best practices\n- Other examples of machine learning and dee
 p learning use-cases around today\n\nLooking forward [10 min]\n- What are 
 some current challenges we have with ML algorithms?\n- What work is being 
 done toward it?\n\nQ&amp;A session [15 min]\n\nSpeaker(s): Jacob George \, Mik
 e Bian\n\nCalgary\, Alberta\, Canada\, Virtual: https://events.vtools.ieee
 .org/m/248126
LOCATION:Calgary\, Alberta\, Canada\, Virtual: https://events.vtools.ieee.o
 rg/m/248126
ORGANIZER:ieeeuofcsb@gmail.com
SEQUENCE:3
SUMMARY:IBM - Basics of Artificial Intelligence Workshop
URL;VALUE=URI:https://events.vtools.ieee.org/m/248126
X-ALT-DESC:Description: &lt;br /&gt;&lt;div dir=&quot;ltr&quot;&gt;Zoom Link:&lt;/div&gt;\n&lt;div dir=&quot;lt
 r&quot;&gt;\n&lt;p&gt;&lt;a href=&quot;https://zoom.us/j/92703439681&quot;&gt;https://zoom.us/j/92703439
 681&lt;/a&gt;&lt;/p&gt;\n&lt;/div&gt;\n&lt;div dir=&quot;ltr&quot;&gt;&amp;nbsp\;&lt;/div&gt;\n&lt;div dir=&quot;ltr&quot;&gt;Workshop
  schedule:&lt;/div&gt;\n&lt;div dir=&quot;ltr&quot;&gt;&amp;nbsp\;&lt;/div&gt;\n&lt;div dir=&quot;ltr&quot;&gt;Intro to AI
  [15 min]&lt;/div&gt;\n&lt;div dir=&quot;ltr&quot;&gt;- What is artificial intelligence?&amp;nbsp\;&lt;
 /div&gt;\n&lt;div dir=&quot;ltr&quot;&gt;- What is machine learning? How is it different?&amp;nbs
 p\;&lt;/div&gt;\n&lt;div dir=&quot;ltr&quot;&gt;- What is deep learning? Include an example&lt;/div
 &gt;\n&lt;div dir=&quot;ltr&quot;&gt;&amp;nbsp\;&lt;/div&gt;\n&lt;div dir=&quot;ltr&quot;&gt;Building your first neural
  network [50 min]&lt;/div&gt;\n&lt;div dir=&quot;ltr&quot;&gt;- Hands on exercise: students will
  build their first neural network to classify images of clothing (i.e. shi
 rts/pants/jackets etc.).&lt;/div&gt;\n&lt;div dir=&quot;ltr&quot;&gt;- Reflection: What does thi
 s teach us about best practices&lt;/div&gt;\n&lt;div dir=&quot;ltr&quot;&gt;- Other examples of 
 machine learning and deep learning use-cases around today&lt;/div&gt;\n&lt;div dir=
 &quot;ltr&quot;&gt;&amp;nbsp\;&lt;/div&gt;\n&lt;div dir=&quot;ltr&quot;&gt;Looking forward [10 min]&lt;/div&gt;\n&lt;div d
 ir=&quot;ltr&quot;&gt;- What are some current challenges we have with ML algorithms?&amp;nb
 sp\;&lt;/div&gt;\n&lt;div dir=&quot;ltr&quot;&gt;- What work is being done toward it?&lt;/div&gt;\n&lt;di
 v dir=&quot;ltr&quot;&gt;&amp;nbsp\;&lt;/div&gt;\n&lt;div dir=&quot;ltr&quot;&gt;Q&amp;amp\;A session [15 min]&lt;/div&gt;
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