Application of Machine Learning in Big Data

Dear Colleagues,

Big data are data that are large and complex and that cannot be processed with traditional methods. Therefore, big data require powerful machine learning models, methods, and algorithms to improve decision-making skills. The use of machine learning with big data can boost several commercial and home applications including health, education, tourism, security, crime control, surveillance, etc.

With the support of authoritative machine learning algorithms, big data can handle and incorporate features of IoT devices to provide inter-connectivity for the media industry, the government, and global industries. Machine learning can detect terrorist activities using big data.

Currently, scalable machine learning architectures can provide faster fault detection to provide the services without interruption. However, there are several challenges of big data to be addressed, such as handling the continuous data growth problems, misperception with big data tool selection, securing data, integrating the data from several different sources, multi-dimensional and multi-variety data issues, etc. These issues can be addressed with properties of machine learning using deep learning, convolutional neural networks, supervised learning, unsupervised learning, reinforcement learning, etc. Thus, the main goal of this Special Issue is to invite high-quality submissions that should consist of original and novel research on the data-driven algorithms for big data, machine intelligence for big data, machine learning classifiers on big data for healthcare fast response, quantum-enhanced machine learning for IoT, drug discovery and toxicology in big data. Additionally, attention will be paid to several big data industry-driven machine learning algorithms.

Prof. Dr. Abdul Razaque
Dr. Mohamed Baza
Dr. Fathi Amsaad
Dr. Bandar Alotaibi
Dr. Munif Alotaibi
Dr. Syed Rizvi
Dr. Mohamed Ben Haj Frej
Guest Editors

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