Continuous Training and Deployment for Machine Learning (ML) at the Edge
Running machine learning (ML) inference in Edge devices close to where the data is generated offers several important advantages over running inference remotely in the cloud. These include real-time processing, lower cost, the ability to work without connectivity and with increased privacy. However, today, implementing an end-to-end ML system for edge inference and continuous deployment …