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Application of Mathematical Models in Linear Algebra to the Metaverse Ecosystem
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Author(s): Özen Özer (Kırklareli University, Turkey), Biswadip Basu Mallik (Institute of Engineering and Management, Kolkata, India)and Gunjan Mukherjee (Brainware University, India)
Copyright: 2023
Pages: 24
Source title:
Handbook of Research on AI-Based Technologies and Applications in the Era of the Metaverse
Source Author(s)/Editor(s): Alex Khang (Global Research Institute of Technology and Engineering, USA), Vrushank Shah (Institute of Technology and Engineering, Indus University, India)and Sita Rani (Department of Computer Science and Engineering, Guru Nanak Dev Engineering College, India)
DOI: 10.4018/978-1-6684-8851-5.ch013
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Abstract
Linear algebra is a branch of mathematics that is widely used throughout science and engineering. Linear algebra includes arithmetic operations with notation sharing. We can be able to have a better understanding of machine learning algorithms only after having a good understanding of linear algebra. Sometimes, machine learning might be pure linear algebra, involving many matrix operations; a dataset itself is often represented as a matrix. Linear algebra is used in data pre-processing, data transformations, and model evaluation. In this chapter, the basic importance of linear algebra has been discussed, and the close liaison of the subject with current research domain in machine learning and data science has been explored in the light of application of the same in solving some critical issues.
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