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ml-trainer

Train a machine learning model on movement data from the micro:bit's accelerometer. Run it on your BBC micro:bit, building your own progam that uses the machine learning model in Microsoft MakeCode.

Try it at https://createai.microbit.org (beta)

History

This repository is derived from ML-Machine (GitHub), a free and open-source interactive machine-learning platform from the Center for Computational Thinking and Design at Aarhus University.

Significant changes have been made to align with the tech stack of other Micro:bit Educational Foundation applications, add and remove features, and revise the user experience for some features also in ML-Machine. We encourage you to review both projects and see which best fits your needs.

Building and running the app

Getting up and running:

  1. Ensure you have a working Node.js environment. We recommend using the LTS version of Node.
  2. Checkout this repository with Git. GitHub have some learning resources for Git that you may find useful.
  3. Install the dependencies by running npm install on the command line in the checkout folder.
  4. Choose from the NPM scripts documented below. Try npm start if you're not sure.

npm run dev

Runs the app in the development mode.

Open http://localhost:3000 to view it in the browser.

The page will reload if you make edits.

This does not show TypeScript or lint errors. Use the eslint plugin for your editor and consider also running npm run typecheck:watch to see full type checking errors.

npm test

Launches the test runner in interactive mode (unless the CI environment variable is defined). See the section about running tests for more information.

npm run build

Builds the app for production to the dist folder.
It correctly bundles React in production mode and optimizes the build for the best performance.

Deployments

Most users should use the supported Foundation deployment at https://createai.microbit.org/

The editor is deployed by GitHub actions.

License

This software is under the MIT open source license.

SPDX-License-Identifier: MIT

Significant code is derived from ML-Machine (also MIT licensed) and is (c) Center for Computational Thinking and Design at Aarhus University and contributors. See individual file copyright notices for more details.

Conceptually this project draws heavily on the work done by the Center for Computational Thinking and Design at Aarhus University (see CCTD.dk) and we're hugely grateful for their ongoing support and collaboration.

We use dependencies via the NPM registry as specified by the package.json file under common Open Source licenses.

Full details of each package can be found by running license-checker:

$ npx license-checker --direct --summary --production

Omit the flags as desired to obtain more detail.

The repository includes forks of Lancaster's micro:bit-samples repositories for micro:bit V1 and V2. They are MIT licensed.

Code of Conduct

Trust, partnership, simplicity and passion are our core values we live and breathe in our daily work life and within our projects. Our open-source projects are no exception. We have an active community which spans the globe and we welcome and encourage participation and contributions to our projects by everyone. We work to foster a positive, open, inclusive and supportive environment and trust that our community respects the micro:bit code of conduct. Please see our code of conduct which outlines our expectations for all those that participate in our community and details on how to report any concerns and what would happen should breaches occur.

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  • TypeScript 77.5%
  • Python 13.1%
  • CMake 5.7%
  • C++ 1.3%
  • JavaScript 1.3%
  • C 0.5%
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