Review of Machine learning: Views, Architectures or Techniques, Challenges and Future guidance and Real-world applications

Abstract

In this digital world, the data is wealth, this data is analyzed, developed and applied to specific applications using some well-developed algorithms known as Machine learning (ML). Machine learning algorithms are supervised, unsupervised, semi-supervised and reinforcement types. Deep learning (DL) is also a method of analyzing the data on a large scale. Deep learning is a further subdivision of The subsection of ML is deep learning and measures a particular type of learning that involves the use of artificial neural networks (ANN). This paper provides group of different machine learning terminologies for quick reference. This study is important to focus on different machine learning techniques and their connection in various real-world applications such as smart cities, cyber security, healthcare, agriculture and intelligent transportation systems. In this paper, machine learning concepts, different types of architectures, the challenges, various real world applications are discussed.