BEGIN:VCALENDAR VERSION:2.0 METHOD:PUBLISH BEGIN:VEVENT ORGANIZER:MAILTO: DTSTART:20210311T170000Z DTEND:20210311T180000Z LOCATION:on24 SUMMARY:Industrial-Grade TinyML Applications with Silicon Labs and Edge Impulse! DESCRIPTION;ENCODING=QUOTED-PRINTABLE:contentimage_195976.png-379x63.png?sv=2016-05-31&sr=b&sig=UlfZWVMjiterLur3veHENPkN6kiWOgGOHMJqDzADSac%3D&se=2026-05-08T23%3A59%3A59Z&sp=r&_=AKcr6Gf+jzHhuHYEeobwFA== WvNba8dqzBb7Khxg== \n \n \n In this hands on demo and workshop we will take a hands on look at the Thunderboard Sense2 Board and TinyML. This workshop is intended to enable you to build a full TinyML application, end-to-end, using the latest best practices in embedded machine learning. You will learn how to collect a dataset, design and train a tiny (but accurate) model, evaluate its performance, optimize it for embedded use, and integrate it into a real embedded application running on a genuine MCU. You will leave this workshop feeling confident that you can solve real world problems using state of the art tinyML—and have fun while you are doing it! \n \n What you will learn by attending: \n \n \n Overview on Industrial-Grade TinyML Applications \n How to collect a dataset \n How to Design and train a tiny (but accurate) model \n How to Evaluate performance, optimize, and integrate ian embedded application \n Live demo using the Thunderboard Sense 2 Board EFR32MG12 \n Q&A Session \n \n \n The presentation will include a live demo using the Thunderboard Sense 2! This will be followed by a Q&A session. \n \n \n contentimage_195978.jpg-248x166.jpg?sv=2016-05-31&sr=b&sig=n8LNwSWU0nMk49X%2Fbqt%2FsfZw2wHIkoAyZ%2FW7K6duawM%3D&se=2026-05-08T23%3A59%3A59Z&sp=r&_=9mikdD26WjB8CuWYc7dieA== \n Buy Now Buy Now \n \n contentimage_195979.png-620x324.png?sv=2016-05-31&sr=b&sig=5cwTCf7yQIWo4C3oGU%2BFEfpx2XhLrepThcHJMG4qNrE%3D&se=2026-05-08T23%3A59%3A59Z&sp=r&_=jegdhK3UlRnlQ2p9htdOoQ== \n \n \n Edge Impulse allows developers to quickly create neural networks across a wide range of Silicon Labs products for free, with integrated deployment to Simplicity Studio. By embedding state-of-the-art TinyML models on EFR32 and EFM32 devices such as MG12, MG21 and GG11, the solution enables: \n \n \n Machine learning \n Real-world sensor data collection and storage \n Advanced signal processing and data feature extraction \n Deep Neural Network (DNN) model training \n Deployment of optimized embedded code \n \n \n The Edge Impulse tool also leverages Edge Impulse's Edge Optimized Neural (EON™) technology to optimize memory use and inference time. \n \n Additional Resources: \n \n \n https://docs.edgeimpulse.com/docs/silabs-thunderboard-sense-2 \n Mini Experimenter: Connected Science Experiments with Casio and IoT by shabaz \n Thunderboard Sense board experience by koudelad \n \n \n The Presenter: \n \n \n \n \n contentimage_195980.jpg-208x208.jpg?sv=2016-05-31&sr=b&sig=guannllJ9CCDJy6tAUigkgq03T7xcceMRRibf83gIpM%3D&se=2026-05-08T23%3A59%3A59Z&sp=r&_=Ok1BPRlyThVOTPfa9II1QA== \n \n \n Jenny Plunkett, User Success Engineer at Edge Impulse \n \n \n Texas Longhorn and software engineer, working as a User Success Engineer at Edge Impulse. Since graduating from The University of Texas I have been working in the IoT space, from customer engineering and developer support for Arm Mbed to consulting engineering for the Pelion platform. X-ALT-DESC;FMTTYPE=text/html:

contentimage_195976.png-379x63.png?sv=2016-05-31&sr=b&sig=UlfZWVMjiterLur3veHENPkN6kiWOgGOHMJqDzADSac%3D&se=2026-05-08T23%3A59%3A59Z&sp=r&_=AKcr6Gf+jzHhuHYEeobwFA==WvNba8dqzBb7Khxg==

 

  

In this hands on demo and workshop we will take a hands on look at the Thunderboard Sense2 Board and TinyML.   This workshop is intended to enable you to build a full TinyML application, end-to-end, using the latest best practices in embedded machine learning. You will learn how to collect a dataset, design and train a tiny (but accurate) model, evaluate its performance, optimize it for embedded use, and integrate it into a real embedded application running on a genuine MCU.  You will leave this workshop feeling confident that you can solve real world problems using state of the art tinyML—and have fun while you are doing it!

 

What you will learn by attending:

 

 

The presentation will include a live demo using the Thunderboard Sense 2!  This will be followed by a Q&A session.

 

 

contentimage_195978.jpg-248x166.jpg?sv=2016-05-31&sr=b&sig=n8LNwSWU0nMk49X%2Fbqt%2FsfZw2wHIkoAyZ%2FW7K6duawM%3D&se=2026-05-08T23%3A59%3A59Z&sp=r&_=9mikdD26WjB8CuWYc7dieA==

Buy NowBuy Now

 

contentimage_195979.png-620x324.png?sv=2016-05-31&sr=b&sig=5cwTCf7yQIWo4C3oGU%2BFEfpx2XhLrepThcHJMG4qNrE%3D&se=2026-05-08T23%3A59%3A59Z&sp=r&_=jegdhK3UlRnlQ2p9htdOoQ==

 

 

Edge Impulse allows developers to quickly create neural networks across a wide range of Silicon Labs products for free, with integrated deployment to Simplicity Studio. By embedding state-of-the-art TinyML models on EFR32 and EFM32 devices such as MG12, MG21 and GG11, the solution enables:

 

 

The Edge Impulse tool also leverages Edge Impulse's Edge Optimized Neural (EON™) technology to optimize memory use and inference time.

 

Additional Resources:

 

 

The Presenter:

 

contentimage_195980.jpg-208x208.jpg?sv=2016-05-31&sr=b&sig=guannllJ9CCDJy6tAUigkgq03T7xcceMRRibf83gIpM%3D&se=2026-05-08T23%3A59%3A59Z&sp=r&_=Ok1BPRlyThVOTPfa9II1QA==
Jenny Plunkett, User Success Engineer  at Edge Impulse
Texas Longhorn and software engineer, working as a User Success Engineer at Edge Impulse. Since graduating from The University of Texas I have been working in the IoT space, from customer engineering and developer support for Arm Mbed to consulting engineering for the Pelion platform.
CLASS:PUBLIC END:VEVENT END:VCALENDAR