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In this video we will see how to build topic model using non negative matrix factorization

NMF stands for non-negative matrix factorization, a technique for obtaining low rank representation of matrices with non-negative or positive elements

we factorize a matrix X into two matrices W and H so that X = WH

The matrix W is generally called the dictionary or basis matrix, and H is known as expansion or coefficient matrix. The underlying idea is that a given data matrix A can be expressed in terms of summation of k basis vectors (columns of W) multiplied by the corresponding coefficients (columns of H)