/maker101

Primary LanguageJavaScriptMIT LicenseMIT

Maker101

Started July 6th, 2022, hopefully ready for April 2023 but may be an ongoing project!

A more in depth look at Machine Learning for High School students or General University Undergrads who have completed Maker100. The Maker101 course uses Arduino C/C++ programming language and the old Arduino IDE (Could use Platform.io, the new Arduino IDE version 2.x or the Arduino Cloud Editor, each IDE has positives and negatives).

Note: this is not yet student tested unlike the maker100 course.

As this is an advanced course teachers, Profs could pick sections relevant to what they are teaching so unlike the Maker100 course this course will be in multiple sections, see individual folders README.md files.

The folders are:

  1. edgeimpulse-keras-expert-mode-for-sensors Advanced EdgeImpulse Keras Expert Mode for Any Sensor
  2. edgeimpulse-wasm-webserial Advanced EdgeImpulse WASM with WebSerial, EdgeImpulse in the browser to a microcontroller (I use the $5 Seedstudio XIAO, but you could even use the Portenta)
  3. ml-kit-nano-33-ble-sense-examples Examples that can be used with the Arduino ML Kit Nano33 Ble Sense that arn't the normal Motion, Sound, Vision Machine Learning examples, but use the other sensors: humidity, temperature, barometric, gesture, proximity, light color and light intensity sensor
  4. software2-1 Advanced After Classification Coding. The issues and possible solutions. I call this software 2.1
  5. tensorflowjs-webserial WebSerial with TensorflowJS: Connecting a Microcontroller ($5 Seedstudio XIAO) for actuators to an (old) Cell Phone running TensorflowJS in the Browser 6.visual-or-auto-ai-coding Visual coding, examples and how to do it, Pros and Cons

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Other Options

So far we have possible curriculum to pick: Slides, Videos, Instructions and COLABS from:

  1. tinyMLx EDx course work here
  2. EdgeImpulse University course work here Download the repository and extract the powerpoint files.
  3. TinyML Harvard
  4. ...

Since these university courses should be: platform, IDE, framework and hardware independent I will put the course work in relevant folders or links:

Arduino-ML-Kit using the Nano33Ble C/C++ link here at the tinyMLx github