Sparse Matrices

Sparse matrices are matrices that contain mostly zero values. In data science and artificial intelligence, sparse matrices are used to efficiently represent and manipulate large datasets that have a lot of missing or irrelevant data. Storing and processing sparse matrices can be much faster and more memory-efficient than dense matrices, which store all values regardless of whether they are zero or not. Sparse matrices are commonly used in applications such as natural language processing, image processing, and recommendation systems. There are several techniques for representing sparse matrices, including the coordinate list (COO) format, compressed sparse row (CSR) format, and compressed sparse column (CSC) format.
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