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Flattening refers to the process of transforming a multi-dimensional structure into a one-dimensional structure, often used in data processing and machine learning to simplify data handling and analysis. It is crucial in neural networks where input data needs to be in a single vector format for efficient computation and learning.
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Row swapping is a fundamental operation in matrix manipulation used to interchange two rows of a matrix, often employed in algorithms like Gaussian elimination to simplify solving linear equations. It is crucial for numerical stability and accuracy, especially when dealing with pivot elements that are zero or near-zero.
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