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Curriculum (Series)

AI/ML at the Edge – Works With 2023

Bringing ML to the edge is necessary. Our AI/ML Works With 2023 track has sessions on building ML into IoT applications with Silicon Labs components and tools.

AI/ML at the Edge- Works With 2023

Artificial intelligence and machine learning (AI/ML) offers device manufacturers across industries and applications a way to introduce feature-rich, low-power products that stand out in the market. To better navigate the need for lower power consumption and size constraints in consumer devices, bringing ML to the edge is necessary. The Works With 2023 AI/ML track featured sessions design specifically to enhance your AI ML skillset and knowledge, with a particular focus on TinyML and enabling ML at the edge.

Check out the courses below to learn how to approach TinyML applications, machine learning techniques, and development requirements for specific AI/ML applications.

AI/ML Sessions:

  1. AIML-101: How to Ensure Success Implementing TinyML Solutions
  2. AIML-102: Machine Health and Condition Monitoring Using the Edge Impulse Platform
  3. AIML-103: Machine Learning Techniques for Predictive Maintenance
  4. AIML-201: ML Development Tools and Building a Voice Controlled Application

 

Featuring the Following Speakers:

Tamas Daranyi
Senior Product Manager,
Silicon Labs

Tristan Cool
Product Marketing Manager,
Silicon Labs

Dan Kozin
Senior Product Manager, IoT Embedded Software,
Silicon Labs

Chris Knorowski
CTO
SensiML

Fill out the form to access the training curriculum.

AI/ML at the Edge- Works With 2023

Artificial intelligence and machine learning (AI/ML) offers device manufacturers across industries and applications a way to introduce feature-rich, low-power products that stand out in the market. To better navigate the need for lower power consumption and size constraints in consumer devices, bringing ML to the edge is necessary. The Works With 2023 AI/ML track featured sessions design specifically to enhance your AI ML skillset and knowledge, with a particular focus on TinyML and enabling ML at the edge.

Check out the courses below to learn how to approach TinyML applications, machine learning techniques, and development requirements for specific AI/ML applications.

Tamas Daranyi
Senior Product Manager,
Silicon Labs

Tristan Cool
Product Marketing Manager,
Silicon Labs

Dan Kozin
Senior Product Manager, IoT Embedded Software,
Silicon Labs

Chris Knorowski
CTO
SensiML

AIML-101: How to Build Edge AI Applications that Work

Over the course of the session, we will present a framework for approaching ML sensor inference modeling and provide valuable takeaways on methods that separate mere demos from production level models.

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AIML-102: Machine Health and Condition Monitoring Using the Edge Impulse Platform

In this session, we cover training and fine-tuning of an audio event detection model using the Edge Impulse platform, with a focus on the Silicon Labs xG24. You will also discover how to deploy the trained model on the edge device, enabling real-time monitoring and analysis of audio events.

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AIML-103: Machine Learning Techniques for Predictive Maintenance

The IoT has already proven itself as revolutionary in the field of machinery condition monitoring, and in this session, we discuss how Silicon Labs hardware can be used to extrapolate time-series machine data at the edge to determine a machine’s remaining useful life.

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AIML-201: ML Development Tools and Building a Voice Controlled Application

Machine learning (ML) is a fast moving and constantly evolving technology, and this session covers how Silicon Labs approaches the ML development workflow, how to choose the most appropriate ML tool for you and your application, and how an ML Expert could quickly build a deep learning application on the EFR32xG24 platform.

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Explore Other Works With Tracks

Watch Every Keynote, Panel, and Technical Session from Works With 2023 Here

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