Difference between revisions of "EverywhereML"
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| − | With everywhereML you can train machine learning models and deploy them on different microcontroller platforms | + | With everywhereML, you can train machine learning models and deploy them on different microcontroller platforms |
https://github.com/eloquentarduino/everywhereml | https://github.com/eloquentarduino/everywhereml | ||
| − | To try out the example download the following | + | To try out the example |
| − | [[Classifier.ipynb.txt]] | + | * download the following python notebook (and change the file type to ipynb - remove .txt) |
| + | [[File:Classifier.ipynb.txt]] | ||
| + | * download the example dataset [[File:Concatenated df 3 led.csv]] | ||
| + | |||
| + | Run the Python notebook and make sure that the path to the data file is adapted in the notebook to fit your local system. | ||
| + | |||
| + | |||
| + | = Alternatives = | ||
| + | * https://github.com/BayesWitnesses/m2cgen | ||
| + | |||
| + | |||
| + | [[Category:Machine Learning]] | ||
Latest revision as of 11:32, 13 June 2024
With everywhereML, you can train machine learning models and deploy them on different microcontroller platforms https://github.com/eloquentarduino/everywhereml
To try out the example
- download the following python notebook (and change the file type to ipynb - remove .txt)
- download the example dataset File:Concatenated df 3 led.csv
Run the Python notebook and make sure that the path to the data file is adapted in the notebook to fit your local system.
