Arduino Machine Learning Tools
Arduino and Edge Impulse have partnered to bring machine learning tools to all Arduino Cloud users with a branded and integrated experience.
The video below contains an example of the full workflow to train a keyword spotting and to run the model on the Arduino Nano 33 BLE Sense using Arduino ML Tools solution:
You can log in the ML Tools platform using your Arduino Cloud credentials. To access the Arduino Machine Learning Tools platform, either go to cloud.arduino.cc or mltools.arduino.cc.
Arduino Cloud home page
Arduino ML Tools SSO
To create a new project, click on your profile picture in the upper right corner and select + Create new project.
Arduino ML Tools - first login
Once you create a project, select the project type you want to build using the helper. You will then arrive on your project's Dashboard:
Arduino ML Tools Dashboard
You can also select which board you are using on the Project Info card, in the bottom-right corner.
The following boards are currently supported in Arduino ML Tools:
*(only using the ingestion sketch and arduino library deployment, latency calculations may not be available)
With everything set up you can now build your first machine learning model with these tutorials:
Looking to connect different sensors? The Data forwarder lets you easily send data from any sensor into Edge Impulse.
Arduino ML Tools Deployment
Once you are happy with the results, please share your project publicly and let everyone knows about it:
Here is an example of the public project made after from the video at the top of this page: Arduino KWS public project.
By default, no password is set for your user profile as you have logged using Arduino Cloud SSO. If you want to use Edge Impulse CLI, you need to set a password. To do so, click on Your profile from the upper-right corner menu:
Arduino ML Tools - Set user password
Last modified 4mo ago