Machine Learning Towards Intelligent Systems: Applications, Challenges, and Opportunities
This paper provides a broad overview of machine learning applications and challenges for researchers and practitioners interested in applying ML to diverse real-world problems.
This review paper explores the applications of machine learning across various domains including education, healthcare, network security, banking and finance, and social media. It identifies unique challenges within these fields and discusses how ML can provide solutions and create new research opportunities.
The emergence and continued reliance on the Internet and related technologies has resulted in the generation of large amounts of data that can be made available for analyses. However, humans do not possess the cognitive capabilities to understand such large amounts of data. Machine learning (ML) provides a mechanism for humans to process large amounts of data, gain insights about the behavior of the data, and make more informed decision based on the resulting analysis. ML has applications in various fields. This review focuses on some of the fields and applications such as education, healthcare, network security, banking and finance, and social media. Within these fields, there are multiple unique challenges that exist. However, ML can provide solutions to these challenges, as well as create further research opportunities. Accordingly, this work surveys some of the challenges facing the aforementioned fields and presents some of the previous literature works that tackled them. Moreover, it suggests several research opportunities that benefit from the use of ML to address these challenges.