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Training and Deploying ML models to STM32 Microcontrollers

Jacob Beningo- Watch Now - Duration: 01:54:12

Machine learning (ML) has often been considered a technology that operates on high-end servers and doesn’t have a place in traditional embedded systems. That perception is quickly changing. This workshop will explore how embedded software engineers can get started with machine learning for microcontroller based systems.

This session balances theory with practical hands-on experience using an STM32 development board.

Attendees will learn:

  • How to collect and classify data
  • Methods available to embedded developers to train a model
  • Hands-on experience training a model
  • How to convert a model to run on an STM32 MCU
  • How to run an inference on a microcontroller

Additional details for development board and tools will be provided closer to the conference.

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No comments or questions yet. Will you be the one who will break the ice?

11:04:01	 From  Michael Kirkhart : Yes
11:04:08	 From  Siva Aduri : yes
11:04:13	 From  Dave Comer : 10-4
11:09:50	 From  Dave Comer : What does AI Compatible mean? Sensors?
11:14:59	 From  rakhel : 0
11:15:01	 From  KN : 1
11:15:02	 From  NateWelch : 0
11:15:08	 From  Dave Comer : Begginer with some knowledge...Tried examples
11:15:09	 From  Devendra Chaudhari : 0
11:15:10	 From  John Phillips : 3
11:15:11	 From  Michael Kirkhart : Trained a model
11:15:16	 From  iiitmk : 3
11:15:19	 From  Al Anway : 1.5
11:15:35	 From  Remco Stoutjesdijk : i bought a book that sits on my desk so i must be a 5
11:15:41	 From  Radu Pralea : 1.(6)
11:15:53	 From  Eduardo Nahmad : Have done some NN and GA, don’t know what number would that correspond to.
11:16:02	 From  Zoltan : 1
11:23:18	 From  Dave Comer : Jason, Do you see LORA used with your ML IoT adventures.
11:23:49	 From  Dave Comer : Connected to CLOUD servers?
11:24:18	 From  Dave Comer : YES!
11:24:34	 From  Dave Comer : How to sign up access?
11:24:53	 From  Michael Kirkhart : The Things Network?
11:24:55	 From  Stephane Boucher : iotonlineconference.com
11:25:00	 From  Dave Comer : :)
11:25:21	 From  Stephane Boucher : Will be launched in a few weeks, will happen early December...
11:47:15	 From  Jacob Beningo : https://github.com/tensorflow/tflite-micro/blob/main/tensorflow/lite/micro/examples/hello_world/create_sine_model.ipynb
11:48:24	 From  Dave Comer : Contents have move from the link you sent but it explains where
11:48:49	 From  Dave Comer : yes
11:54:07	 From  Michael Kirkhart : Note: you need to be logged into a Google account to run the example.
12:01:34	 From  Dave Comer : How do you save your file(s) locally again?
12:02:10	 From  Dave Comer : Thanks
12:13:05	 From  Dave Comer : I'm done, but don't have a system avail. Will follow along as you go...
12:14:32	 From  Al Anway : watching only
12:18:33	 From  John Phillips : Not to dampen the enthusiasm too much, but all this is effectively a low-pass filter that cleaned up a sinewave waveform ?
12:19:50	 From  Dave Comer : But, when applied to an FFT
12:21:55	 From  KN : yes
12:49:35	 From  Stephane Boucher   to   Jacob Beningo(Direct Message) : We'll need to wrap things up very soon.  Jenny's talks tarts in 10 minutes and it is done live on Zoom...
12:52:40	 From  Michael Kirkhart : Nice to see that ST has a version of STM32CubeIDE that runs native on Mac and linux.
12:53:13	 From  Michael Kirkhart : It was not too long ago that many dev tools were Windows only.
12:54:09	 From  Michael Kirkhart : What is the difference between Tensorflow Lite and TinyML?