A brief survey of machine learning methods and their sensor and IoT applications
Published on Aug 1, 2017
· DOI :10.1109/iisa.2017.8316459
This paper provides a brief survey of the basic concepts and algorithms used for Machine Learning and its applications. We begin with a broader definition of machine learning and then introduce various learning modalities including supervised and unsupervised methods and deep learning paradigms. In the rest of the paper, we discuss applications of machine learning algorithms in various fields including pattern recognition, sensor networks, anomaly detection, Internet of Things (IoT) and health monitoring. In the final sections, we present some of the software tools and an extensive bibliography.