Welcome to Edge Impulse! We enable developers to create the next generation of intelligent device solutions with embedded Machine Learning. In the documentation you'll find user guides, tutorials and API documentation. For support, visit the forums.
If you're new to the idea of embedded machine learning, or machine learning in general, you may enjoy our quick guide: What is embedded ML, anyway?
Get started with any device
Follow these three steps to build your first embedded Machine Learning model - no worries, you can use almost any device to get started.
If you want to collect live data from a supported development kit, select your board from the list of fully supported development boards and follow the instructions to connect your board to edge impulse.
If you already have a dataset, you can upload it via the Uploader.
If you have a mobile phone you can use it as a sensor to collect data, see Mobile phone.
After training your model you can run your model on your device:
If you want to integrate the model with your own firmware or project you can export your complete model (including all signal processing code and machine learning models) to a C++ or Arduino library with no external dependencies (open source and royalty-free), see Running your impulse locally.
If you have a fully supported development board (or your mobile phone) you can build new firmware - which includes your model - directly from the UI. It doesn't get easier than that!
Suitable for any type of embedded ML application
We have some great tutorials, but you have full freedom in the models that you design in Edge Impulse. You can plug in new signal processing blocks, and completely new neural networks. See Building custom processing blocks, or click the three dots on a neural network page and select 'Switch to Keras (expert) mode'.
For larger teams, and companies with lots of data we offer an enterprise version of Edge Impulse. The enterprise version offers team collaboration on projects, a dataset builder that makes your internal data available to your whole team, integrations with your cloud buckets, transformation blocks that let you extract ML features from thousands of files in one go, and custom processing and deployment blocks for your organization. You can find documentation under Organizations or contact us via [email protected] for more information.