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Linear Interpolation

Linear interpolation is a mathematical method for estimating unknown values that lie between two known data points by assuming a straight-line relationship. It is widely used in computer graphics, data analysis, and numerical methods to create smooth transitions or fill in missing data. The technique calculates intermediate values using a simple weighted average based on the distance from the known points.

Also known as: Lerp, Linear Interp, Linear Extrapolation, Bilinear Interpolation, Linear Blend
🧊Why learn Linear Interpolation?

Developers should learn linear interpolation for tasks involving smooth animations, data smoothing, or estimating values in datasets, such as in game development for moving objects between frames or in data science for imputing missing values. It is essential in graphics programming for rendering gradients and in simulations where continuous values are needed from discrete samples, providing a computationally efficient way to approximate intermediate states.

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