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DTSTAMP:20260107T213249Z
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DTSTART;TZID=America/Denver:20251021T085000
DTEND;TZID=America/Denver:20251023T101500
DESCRIPTION:Join us for a fast-paced 2-day TinyML workshop where machine le
 arning meets the real world at the edge. You’ll build end-to-end\, senso
 r-driven applications on microcontrollers that run efficient AI models in 
 real time. Through guided labs\, you’ll collect data from front-end sens
 ors and engineer features\, quantize and compress models\, and deploy them
  using Python toolchains and embedded runtimes.\n\nBring curiosity\, a lap
 top\, and your favorite ideas—we’ll supply boards\, sensors\, starter 
 notebooks\, and reference code. Leave with deployable TinyML prototypes\, 
 a repeatable pipeline\, and the confidence to take edge AI from concept to
  product.\n\nThis workshop assumes participants already understand core ma
 chine learning concepts and can train and evaluate models in Python\; we
 ’ll focus our time on edge-specific workflows rather than introductory m
 aterial.\n\nCoffee\, snacks\, and good vibes included\, too.\n\nCo-sponsor
 ed by: Boise State University\n\nAgenda: \nDay 01: October 21st\n\nTime	Ag
 enda\n8:50 AM	Breakfast &amp; sign-in (light snacks)\n9:00 AM	Session: DEPLOYI
 NG A KEY WORD SPOTTING MODEL IN ARDUINO IDE AND TRAINING YOUR OWN DATA WIT
 H EDGE IMPULSE\n10:15 AM	closing remarks\nDay 02: October 23rd\n\nTime	Age
 nda\n8:50 AM	Breakfast &amp; sign-in (light snacks)\n9:00 AM\nSession: DEPLOYI
 NG A KEY WORD SPOTTING MODEL IN ARDUINO IDE AND TRAINING YOUR OWN DATA WIT
 H EDGE IMPULSE (cont.)\n\nSession: TRAINING AND DEPLOYING A GESTURE DETECT
 ION MODEL\n\n10:15 AM	closing remarks\n\nRoom: Glassroom\, Bldg: Albertson
 s Library\, The SPACE\, 1865 W Cesar Chavez Ln\, Boise\, ID 83725\, Boise\
 , Idaho\, United States\, 83725
LOCATION:Room: Glassroom\, Bldg: Albertsons Library\, The SPACE\, 1865 W Ce
 sar Chavez Ln\, Boise\, ID 83725\, Boise\, Idaho\, United States\, 83725
ORGANIZER:omiya.h@ieee.org
SEQUENCE:49
SUMMARY:Machine learning on edge: TinyML workshop! 
URL;VALUE=URI:https://events.vtools.ieee.org/m/504732
X-ALT-DESC:Description: &lt;br /&gt;&lt;p&gt;Join us for a fast-paced 2-day TinyML work
 shop where machine learning meets the real world at the edge. You&amp;rsquo\;l
 l build end-to-end\, sensor-driven applications on microcontrollers that r
 un efficient AI models in real time. Through guided labs\, you&amp;rsquo\;ll c
 ollect data from front-end sensors and engineer features\, quantize and co
 mpress models\, and deploy them using Python toolchains and embedded runti
 mes.&lt;/p&gt;\n&lt;p&gt;Bring curiosity\, a laptop\, and your favorite ideas&amp;mdash\;w
 e&amp;rsquo\;ll supply boards\, sensors\, starter notebooks\, and reference co
 de. Leave with deployable TinyML prototypes\, a repeatable pipeline\, and 
 the confidence to take edge AI from concept to product.&lt;/p&gt;\n&lt;p&gt;&lt;em&gt;&lt;stron
 g&gt;This workshop assumes participants already understand core machine learn
 ing concepts and can train and evaluate models in Python\; we&amp;rsquo\;ll fo
 cus our time on edge-specific workflows rather than introductory material.
 &lt;/strong&gt;&lt;/em&gt;&lt;/p&gt;\n&lt;p&gt;Coffee\, snacks\, and good vibes included\, too.&lt;/p
 &gt;&lt;br /&gt;&lt;br /&gt;Agenda: &lt;br /&gt;&lt;p&gt;&lt;strong&gt;&lt;span style=&quot;color: rgb(0\, 0\, 0)\;
 &quot;&gt;Day 01: October 21st&lt;/span&gt;&lt;/strong&gt;&lt;/p&gt;\n&lt;table style=&quot;border-collapse:
  collapse\; width: 100%\;&quot; border=&quot;1&quot;&gt;&lt;colgroup&gt;&lt;col style=&quot;width: 21.806%
 \;&quot;&gt;&lt;col style=&quot;width: 78.194%\;&quot;&gt;&lt;/colgroup&gt;\n&lt;tbody&gt;\n&lt;tr&gt;\n&lt;td&gt;&lt;strong&gt;
 Time&lt;/strong&gt;&lt;/td&gt;\n&lt;td&gt;&lt;strong&gt;Agenda&lt;/strong&gt;&lt;/td&gt;\n&lt;/tr&gt;\n&lt;tr&gt;\n&lt;td&gt;8:5
 0 AM&lt;/td&gt;\n&lt;td&gt;Breakfast &amp;amp\; sign-in (light snacks)&lt;/td&gt;\n&lt;/tr&gt;\n&lt;tr&gt;\n
 &lt;td&gt;9:00 AM&lt;/td&gt;\n&lt;td&gt;Session: DEPLOYING A&amp;nbsp\; KEY WORD SPOTTING MODEL 
 IN ARDUINO IDE AND TRAINING YOUR OWN DATA WITH EDGE IMPULSE&lt;/td&gt;\n&lt;/tr&gt;\n&lt;
 tr&gt;\n&lt;td&gt;10:15 AM&lt;/td&gt;\n&lt;td&gt;closing remarks&lt;/td&gt;\n&lt;/tr&gt;\n&lt;/tbody&gt;\n&lt;/table
 &gt;\n&lt;p&gt;&lt;strong&gt;Day 02: October 23rd&lt;/strong&gt;&lt;/p&gt;\n&lt;table style=&quot;border-coll
 apse: collapse\; width: 100%\;&quot; border=&quot;1&quot;&gt;&lt;colgroup&gt;&lt;col style=&quot;width: 21
 .806%\;&quot;&gt;&lt;col style=&quot;width: 78.194%\;&quot;&gt;&lt;/colgroup&gt;\n&lt;tbody&gt;\n&lt;tr&gt;\n&lt;td&gt;&lt;st
 rong&gt;Time&lt;/strong&gt;&lt;/td&gt;\n&lt;td&gt;&lt;strong&gt;Agenda&lt;/strong&gt;&lt;/td&gt;\n&lt;/tr&gt;\n&lt;tr&gt;\n&lt;t
 d&gt;8:50 AM&lt;/td&gt;\n&lt;td&gt;Breakfast &amp;amp\; sign-in (light snacks)&lt;/td&gt;\n&lt;/tr&gt;\n&lt;
 tr&gt;\n&lt;td&gt;9:00 AM&lt;/td&gt;\n&lt;td&gt;\n&lt;p&gt;Session: DEPLOYING A&amp;nbsp\; KEY WORD SPOTT
 ING MODEL IN ARDUINO IDE AND TRAINING YOUR OWN DATA WITH EDGE IMPULSE (con
 t.)&lt;/p&gt;\n&lt;p&gt;Session: TRAINING AND DEPLOYING A GESTURE DETECTION MODEL&lt;/p&gt;\
 n&lt;/td&gt;\n&lt;/tr&gt;\n&lt;tr&gt;\n&lt;td&gt;10:15 AM&lt;/td&gt;\n&lt;td&gt;closing remarks&lt;/td&gt;\n&lt;/tr&gt;\n&lt;
 /tbody&gt;\n&lt;/table&gt;
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