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MathWorks Seminars & Workshops Day 2


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Date:  Thu, September 01, 2022
Time:  10:00am
Location:  Holmes 244
Speaker:  MathWorks Engineers: Reece Teramoto and Esperanza Linares

Offered by The MathWorks, Inc.

Intro to Deep Learning and IoT with MATLAB (Workshop)
Thursday, September 1st at 10 am
Follow this link to register as seats are limited!

In this workshop, you will perform object detection and classification on everyday objects that are captured using a web camera. After objects are recognized and classified, a label is associated with the object. These labels are then sent to a channel via the internet of things (IoT) for further analysis. Our goal for this workshop is: to show our participants how easy it is to get started with Deep Learning and the IoT. 

After the workshop, you can explore using what you have learned as a framework for your Deep Learning and/or IoT projects. 

Bring your laptop!
In one hour, you will perform object detection and classification on everyday objects that are captured using a web camera. After objects are recognized and classified, a label is associated with the object. These labels are then sent to a channel via the internet of things (IoT) for further analysis. Our goal for this workshop is: to show our participants how easy it is to get started with Deep Learning and the IoT. 

After the workshop you can explore using what you have learned as a framework for your own Deep Learning and/or IoT projects. 

Lunch and Office Hours with MathWorks Engineers
Thursday, September 1st at 12pm
Follow this link to register as seats are limited!

Working with Messy Data / Tackling Big Data with MATLAB
Thursday, September 1st at 1pm
Follow this link to register as seats are limited!

Analyzing real-world data can get messy! This session is intended to show how to get ugly, real-world data into MATLAB and get it ready for analysis, as well as learn strategies and techniques for handling large amounts of data in MATLAB. With flight-test data as an example, the content in this presentation is meant to help engineers with the following key items:
Highlights:
  • Key updates to the MATLAB environment, capabilities, data-types, etc.
  • Importing data (large data sets, varying formats)
  • Data Management (efficient storage/access strategies)
  • Handling Missing or Misaligned Data
  • Detecting and Handling Outliers
  • Smoothing and Filtering Noisy Data
  • Leveraging tall arrays to analyze and process data that does not fit in memory
  • Using Parallel Computing Toolbox for increased performance
MATLAB and Simulink are registered trademarks of The MathWorks, Inc.

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