The Gauss-Seidel Method is an iterative algorithm used for solving systems of linear equations, particularly useful for large sparse matrices. It updates the solution of the variables sequentially, using the most recent values, making it efficient and suitable for applications like optimization in data science. This method is important in numerical analysis as it provides a way to handle cases where direct methods like Gaussian elimination are computationally expensive or impractical.
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