Vaibhav Narawade*

Professor, Department of Computer Technology, Ramrao Adik Institute of Technology, Nerul, Navi Mumbai, India

*Corresponding Author: Vaibhav Narawade, Professor, Department of Computer Technology, Ramrao Adik Institute of Technology, Nerul, Navi Mumbai, India.

Received: December 16, 2022; Published: January 20, 2023

Abstract

Machine learning has been extensively researched during the last two decades. This is often driven by the need to automate the process of knowledge acquired during the development of expert systems. Machine learning has lately received attention in the context of data mining and knowledge discovery. Much machine learning research has focused on classification learning. Inductive learning, which is one of the most mature and commonly used machine learning algorithms presently accessible, is given special emphasis. Machine learning covers the subject of how to develop machines that learn on their own. It is one of today's fastest-expanding technological topics, located at the crossroads of computer science and statistics, as well as at the heart of artificial intelligence and data science. The adoption of data-intensive machine-learning approaches may be seen as leading to more evidence-based decision-making in a variety of fields such as health care, manufacturing, education, financial modeling, police, and marketing. Emerging trends are highlighted, and problems in our everyday lives are handled using machine learning (ML) models such as Artificial Neural Networks, K-Nearest Neighbors, Logistic Regression, and Support Vector Machines. This study focuses on forthcoming developments and security paradigms in machine learning. The study discusses malware analysis and detection skills by comparing prior samples. The paper explores emerging trends and machine learning applications.

Keywords:Algorithm; Machine Learning; Internet

References

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Citation

Citation: Vaibhav Narawade. “New Trends in Machine Learning Expected to Emerge in 2022".Acta Scientific Computer Sciences 5.2 (2023): 74-76.

Copyright

Copyright: © 2023 Vaibhav Narawade. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.