Comprehensive Review on Machine Learning Applications in Cloud Computing

Sampada Zende; Tanisha Singh; Mahendra Suryavanshi

Abstract

Cloud computing provides on-demand access to a variety of processing, storage, and network resources. Over the past few years, cloud computing has become a widely accepted computing paradigm and one of the fastest-growing model in the IT industry. It turns out to be a new computing evolution after the evolution of mainframe computing, client-server computing and mobile computing. Cloud computing model faces various challenges such as security, resource allocation, load balancing, incast, interoperability. Machine learning is the study of computer algorithms that get better on their own via experience. Algorithms for machine learning are strong analytical techniques that let computers see patterns and help people learn. In this review paper, we present an analysis of various cloud computing issues and machine learning algorithms. Furthermore, we have comprehensively analyzed applications of numerous machine learning algorithms that are used to mitigate a variety of cloud computing issues.

Keywords

Supervised Learning, Unsupervised Learning, Cloud Security, Resource Allocation, Load Balancing

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Cites this article as

S. Zende, T. Singh, M. Suryavanshi, "Comprehensive Review on Machine Learning Applications in Cloud Computing", International Journal of Innovative Research in Computer Science and Technology (IJIRCST), Vol-12, no.4, pp.16-24, 2024. Available from: https://doi.org/10.55524/ijircst.2024.12.4.3

Corresponding Author

Sampada Zende

MSc. Computer Science Student, Computer Science and Applications, Dr. Vishwanath Karad MIT World Peace University, Pune, Pune, India

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