Edge Impulse Docs

Edge Impulse Documentation

Welcome to the Edge Impulse documentation. You'll find comprehensive guides and documentation to help you start working with Edge Impulse as quickly as possible, as well as support if you get stuck. Let's jump right in!

Getting Started

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.

  1. You'll need some data:
  2. Try the tutorials on continuous motion recognition, recognizing sounds from audio or adding sight to your sensors. These will let you build machine learning models that detect things in your home or office.
  3. 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!
    • If you have a gateway, a computer or a web browser where you want to run your model, you can export to WebAssembly and run it anywhere you can run JavaScript.

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'.

API Documentation

You can access any feature in the Edge Impulse Studio through the Edge Impulse API. For example, you can use this to build your own AutoML pipeline which finds the best parameters for your signal processing code - see Parameter search with Python for a tutorial. We also have the Ingestion service if you want to send data directly, and we have an open Remote management protocol to control devices from the Studio.

Enterprise version

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.

Updated 15 days ago

Getting Started

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