LINEAR ALGEBRA IN MACHINE LEARNING, ROBOTICS AND COMPUTER VISION

Abstract

Linear algebra is fundamental to machine learning, robotics, and computer vision, providing the mathematical foundation for data representation, model training, optimization, transformations, and complex computations. Its extensive applications, ranging from basic data preprocessing to advanced algorithm development and system design, make it indispensable for developing and implementing technologies in these fields.Wavelets and Haar matrices plays a crucial role in compressing as well as processing audio and video signals.Various different methods are also used to deal with the problem of curve interpolation.We have also discussed about vector norms which is used to evaluate model’s error or reduce model’s complexity.The versatility of Singular Value Decomposition(SVD) in data compresssion, particularly in image processing, solve problems like least square optimization, dimensionality reduction(PCA),pattern recognition and approximation also cannot be neglected.