ABSTRACT
The chapter starts with Unsupervised models design and apply Model Connectivity Hardware Design as part of the Machine Learning models. Unsupervised models discussed as part of the chapter includes K-Means Cluster and Hierarchical Clusters. Each of the Unsupervised models discussed as part of the chapter analyzed from extremely Constrained Devices (xCDs) and environment perspective and then goes in depth to optimize the Machine Learning model to be effectively functional in the constrained environment. The constrained environment modeling includes Hardware Connectivity Trade-offs, Connectivity Model Trade-offs, and Hardware Connectivity Trade-offs. By following the procedures and the frameworks described as part of the chapter, the Machine Learning and Embedded Engineers can develop machine learning models and analyze holistically to successfully deploy in resource constrained environments.
