A sparse matrix is a type of matrix in which most of the elements are zero. This characteristic makes it different from a dense matrix, where most elements are non-zero. Sparse matrices are commonly used in various fields, such as computer science, engineering, and data science, to efficiently represent large datasets without wasting memory on zero values. To store a sparse matrix efficiently, specialized data structures like compressed sparse row (CSR) or coordinate list (COO) formats are often used. These formats only keep track of the non-zero elements and their positions, allowing for faster computations and reduced storage requirements. Sparse matrices are particularly useful in applications like machine learning, graph theory, and scientific computing.