machine learning

IOT Developer Day

Developer Day is a free full-day professional development event - featuring coding, building, learning, and a career fair.  The RIOT.org-sponsored event is geared towards those in the trenches, building IoT solutions in hardware, software and IT systems - but with multiple session tracks, so there's something for everyone.  Chris from Phase Dock will be presenting solutions

2021-08-28T11:53:18-04:00|

Machine Learning Demystified – Part 3

What about using microcontrollers to run machine learning models? Microcontrollers are less resource constrained than they used to be, and can be augmented with single-board computers. What does this mean for the field? This is a transcript of Phase Dock LIVE, December 12, 2020 with Chris Lehenbauer and Brandon Satrom. It has been edited

2021-02-26T14:43:21-05:00STEM Education, Technology|

Machine Learning Demystified – Part 2

Can you give us a couple of real-world examples of some useful machine learning in industry or for other fields? Where do you use machine learning? What for? This is a transcript of Phase Dock LIVE, December 12, 2020 with Chris Lehenbauer and Brandon Satrom. It has been edited for length, clarity and readability.

2021-01-13T14:08:11-05:00STEM Education, Technology|

Machine Learning Demystified – Part 1

How does machine learning (ML) work? Can tiny computers drive IOT and ML at the edge? How can I get started with ML? Learn all that and more about the collaboration between IOT, tiny computers and machine learning. This is a transcript of Phase Dock LIVE, December 12, 2020 with Chris Lehenbauer and Brandon

2021-01-13T14:06:55-05:00STEM Education, Technology|

Phase Dock LIVE with Brandon Satrom “Demystifying Machine Learning”

Join Chris for Phase Dock LIVE Featuring Brandon Satrom and Machine Learning Demystified: For Students of All Ages For the video, transcripts and other resources, see our Blog posts. Part One: Introductions and the Theory of Machine Learning. Part Two: Real-world examples and practical ideas to get started with Machine Learning. Part Three: Machine Learning

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