Machine Learning Technique and Applications – An Classification Analysis

Abstract

The digitally-enhanced environment is susceptible to massive data, such as information security data, internet technology data, cellular internet, patient records, media data, corporate data, and so on, in the current era of Industry 4.0. Understanding of Machine Learning (ML) is essential for intelligently evaluating these sets of data and developing related "intelligent" and "automated" solutions. Different forms of ML algorithms e.g. reinforcement learning, semi-supervised, unsupervised and supervised learning exist in this segment. In addition, deep learning, which is a wider segment of ML techniques, can smartly evaluate datasets on a massive scale. In this research, a comprehensive analysis of ML techniques and classification analysis algorithms that are applicable to develop capabilities and intelligence of applications are analyzed. Therefore, this research’s contribution is illustrating the key principles of various ML techniques and their application in different real-life application realms e.g. e-commerce, healthcare, agriculture, smart cities, cyber-security systems etc. Lastly, this paper presents a discussion of the challenges and future research based on this research.