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VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
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TZID:America/Phoenix
BEGIN:STANDARD
DTSTART:19671029T010000
TZOFFSETFROM:-0600
TZOFFSETTO:-0700
TZNAME:MST
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BEGIN:VEVENT
DTSTAMP:20260414T144820Z
UID:39005DD2-9D58-4364-B236-5AD7AC89FD1A
DTSTART;TZID=America/Phoenix:20260413T163000
DTEND;TZID=America/Phoenix:20260413T183000
DESCRIPTION:AI is quickly becoming embedded in everyday applications. It’
 s becoming essential for students and educators to adopt this technology t
 o solve complex real-world problems. MATLAB and Simulink provide a flexibl
 e and powerful platform to develop and automate data analysis\, deep learn
 ing\, AI\, and simulation workflows in a wide range of domains and industr
 ies. In this workshop we will introduce deep learning with MATLAB. We will
  utilize a previously trained network and modify it\, using the MATLAB Dee
 p Network Designer. The Deep Network Designer allows you to interactively 
 build\, visualize\, and train neural networks. Individuals can generate th
 e code for the neural network and finetune parameters. Users can use popul
 ar pre-trained networks or construct their own. We will also look at the M
 ATLAB Classification Learner to run several models on a single data set. T
 hese visual approaches create a more efficient workflow.\n\nCo-sponsored b
 y: IEEE Student Branch at ASU\n\nSpeaker(s): Jon\, \n\nRoom: 152\, Bldg: P
 SH\, The George M. Bateman Physical Sciences Center\, H Wing\, 525 E Unive
 rsity Dr\, Tempe\, Arizona\, United States\, 85281
LOCATION:Room: 152\, Bldg: PSH\, The George M. Bateman Physical Sciences Ce
 nter\, H Wing\, 525 E University Dr\, Tempe\, Arizona\, United States\, 85
 281
ORGANIZER:chao.wang.6@asu.edu
SEQUENCE:24
SUMMARY:AI with MATLAB: From raw data to trained models
URL;VALUE=URI:https://events.vtools.ieee.org/m/553341
X-ALT-DESC:Description: <br /><p>AI is quickly becoming embedded in everyda
 y applications. It&rsquo\;s becoming essential for students and&nbsp\;educ
 ators to adopt this technology to solve complex real-world problems. MATLA
 B and Simulink provide&nbsp\;a flexible and powerful platform to develop a
 nd automate data analysis\, deep learning\, AI\, and&nbsp\;simulation work
 flows in a wide range of domains and industries. In this workshop we will 
 introduce&nbsp\;deep learning with MATLAB. We will utilize a previously tr
 ained network and modify it\, using the&nbsp\;MATLAB Deep Network Designer
 . The Deep Network Designer allows you to interactively build\,&nbsp\;visu
 alize\, and train neural networks. Individuals can generate the code for t
 he neural network and finetune&nbsp\;parameters. Users can use popular pre
 -trained networks or construct their own. We will also look&nbsp\;at the M
 ATLAB Classification Learner to run several models on a single data set. T
 hese visual approaches&nbsp\;create a more efficient workflow.</p>
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