Software Engineering for Embedded Systems, 2nd Edition

15

Machine Learning at the Edge

Markus Levy    NXP Semiconductors, Eindhoven, The Netherlands

Abstract

In this chapter we start by introducing machine learning (ML). We explain the terminology such as supervised and unsupervised ML. We explain the ML tasks called classification and regression. Then we introduce algorithms such as nearest neighbor or support vector machine (SVM), and speak about decision trees and in reference to an example of decision trees we explain ensemble techniques as well as boosting and bagging techniques.

Keywords

Artificial intelligence; Machine learning; Semantic gap; Data augmentation; Neural network; Classification; Regression; CNN; RNN

Chapter Outline

• 1 Introduction    
  • 1.1 Coding Examples    
  • 1.2 The Machine Learning Revolution     ...