Creating a machine learning (ML) model and deploying it to an embedded device requires a lot of steps to take: From collecting and storing data, to using data processing tools, to training in yet another platform, to converting into a format for specific embedded hardware, to flashing firmware for deployment. Historically, this was not a quick nor reliable endeavor for early practitioners of machine learning.

Edge Impulse Studio was built to consolidate and standardize this entire workflow. Our cloud-based platform makes it easy to build, train, and deploy machine learning models for edge devices all in one place, while providing visibility and features that greatly enhance the MLOps process and its capabilities for the user. Designed for engineers and developers whether they’re building a product or just picking up ML for the first time, it streamlines the entire workflow — from data collection to deployment — using an intuitive web interface.

Getting started in Edge Impulse is s...