Linear Transformation is a central concept in linear algebra that provides a systematic way to study relationships between vector spaces. It plays a vital role in simplifying complex mathematical structures and modeling real-world phenomena. This research paper presents a detailed and descriptive study of linear transformations, including their theoretical foundation, properties, and significance. The paper further explores diverse real-life applications such as computer graphics, engineering systems, physics, economics, robotics, and data science. Through explanatory discussions and illustrative examples, the study demonstrates how linear transformations serve as powerful tools in both theoretical and applied disciplines.
Linear Transformation, Vector Spaces, Matrix Representation, Kernel, Range, Eigenvalues, Computer Graphics, Data Science, Engineering Applications.
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