This presentation will first highlights some basic training techniques, such as data augmentation, but the primary focus will be on various ways to deploy neural network frameworks and classical machine learning algorithms, and most importantly, utilizing a variety of open source tools and techniques. We will show how these techniques fit in with some real use cases such as object recognition and anomaly detection. The hands-on session portion of the class will allow attendees to take a trained neural network model and deploy it on a i.MX 8M. Attendees will utilize the Linux development environment and implement an end-to-end use case.
