Developing on Edge Impulse
As we talked about in the previous chapter, developing a TinyML application requires many steps, such as collecting requirements and data, pre-processing data, model development and optimization, deployment, performance tracking, and maintenance. In a traditional software project, we have DevOps to manage the software life cycle. When it comes to machine learning, we define Machine Learning Operations or MLOps. An MLOps platform provides us with the tools and resources to design, develop, and maintain our machine learning applications. What makes an MLOps platform different from a DevOps platform is that it also manages data and the resulting models in its versioning subsystem.
Edge Impulse is the leading MLOps platform for TinyML. It helps at every step of the ML application development process. Some important features of Edge Impulse are the following:
- A web-based development environment, Edge Impulse Studio, to manage the entire ML life...
