Deep Learning with Raspberry Pi and MATLAB


Do you want to take your deep learning algorithms beyond desktop and apply them in real-world systems?

In this webinar, we will show how MATLAB can be used to deploy your deep learning algorithms onto a Raspberry Pi. We will also cover a technique called transfer learning that allows you to retrain existing networks to perform custom prediction tasks.  

We will use a real-world computer vision example to demonstrate how to deploy deep learning networks and perform inference tasks on your embedded hardware.


  • Generate C/C++ code from deep learning networks as inference engines for Raspberry Pi.
  • Access peripherals from the Raspberry Pi for use in MATLAB with the generated code

Please allow approximately 45 minutes to attend the presentation and Q&A session. We will be recording this webinar, so if you can't make it for the live broadcast, register and we will send you a link to watch it on-demand.

About the Presenter

Madhu Govindarajan works as a Technical Marketing Engineer at the MathWorks and focuses on hardware connectivity with MathWorks tools. Prior to joining MathWorks, Madhu interned with Honda R&D Americas while working toward a master’s degree in mechanical engineering at The Ohio State University.

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