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Graphics and animation: 3D models, projections, and transformations use matrices from linear algebra for realistic visuals in movies, games, and even weather animations.
Image and video processing: Compressing images for faster sharing, noise reduction in photos, and even facial recognition rely on linear algebra algorithms.
Data analysis and statistics: Regression models for predicting trends, analyzing financial markets, and understanding scientific data all involve solving linear systems using linear algebra.
Robotics and control systems: Robots use it for positioning, path planning, and even balancing themselves.
Machine learning and artificial intelligence: Many algorithms behind AI, like recommendation systems and image classification, depend heavily on linear algebra concepts.
Computer graphics: From 3D modeling to animation, linear algebra is crucial for manipulating and projecting objects in virtual spaces.
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Linear algebra finds applications in various real-life scenarios such as image processing, engineering (like designing electrical circuits), data analysis (in fields like finance and economics), and even in computer graphics for animation and gaming, where concepts like vectors, matrices, and transformations are extensively used for problem-solving and modeling real-world situations.
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Suppose you go to your friend and ask him to loan his bike to you. He will calculate price (P) based on various factors such as fuel price (x), maintenance (y), and profit (z). He will keep a margin on every factor to calculate a reasonable price. This is algebra which finds relations through equations/inequalities.
knowingly or unknowingly we use algebra in everyday life.
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