Machine learning techniques will contribution to making Internet of Things (IoT) applications that are considered the most significant sources of new data in the coming future more intelligent, where the systems will be able to access raw data from different resources over the network and analyze this information in order to extract knowledge. This study focuses on supervised machine learning techniques that is considered the main pillar of the IoT smart data analysis. This study includes reviews and discussions of substantial issues related to supervised machine learning techniques, highlighting the advantages and limitations of each algorithm, and discusses the research trends and recommendations for further study.
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