A set of hardware independent web-page, client-side (No Internet required) programming tools to help bring Machine Learning Proof of Concept's to more students, by using the power of the web with javascript-tensorflowJS and the simplicity of the C/C++ microcontroller serial print command combined together using Google's WebSerial that works on any desktop (or laptop) computer.

Note: WebSerial using a polyfill works on a few Android phones such as some of the Google Pixel phones.

Demos

Skip to basic instructions

Acceleration x,y,z time-series Demos: Now works for any sensor other than Vision and Sound

1. Best acceleration

Note: This is also for other sensors! Always the best so far x,y,x acceleration page. CSV and Senses work and ML works, classification works, cell phone (Apple & Android) motion works



2. Next Acceleration Draft: any data in the textarea can be used to make a ML model, so I am testing the mouse x y location data

Basic instructions

• This is a hardware independent proof of concept. Use a sensor or two and get a Machine Learning Keras model working with an actuator on any microcontroller board.
• Once you know your model works, slow down and record your data into a CSV file for uploading to a professional cloud Machine Learning service like edgeImpulse.com or Arduino Cloud or just stay client-side with tinyMLjs and build another model.
• If you are staying with tinyMLjs, upload the CSV files to a model designer, train the model and save your tensorflowJS saved model
• If you are still staying with tinyMLjs (wow you are great!) load the saved model onto a webpage with webSerial connection to your actuator and test how well your =model works in real world settings.
• Or use the conversion program either downloaded to online that converts the TensorflowJS saved model into tensorflowLite format and then use xxd -i to convert the binary file into a c-header file that can be installed onto your microcontroller using your IDE or the Arduino IDE.

Made by Jeremy Ellis. Twitter @rocksetta, or @rocksetta@masto.ai or GitHub profile at https://github.com/hpssjellis. Use tinyMLjs at your own risk! Design By Max S. Github at https://github.com/maxbiz100

Started Jun 4th, 2023 Version 0.1.0-2