numpy.dot — NumPy v2.1 Manual
numpy.dot# numpy.dot(a, b, out=None)# Dot product of two arrays. Specifically, If both a and b are 1-D arrays, it is inner product of vectors (without complex conjugation). If both a and b are 2-D arrays, it is matrix multiplication, but using matmul or a @ b is preferred. If either a or b is 0-D (scalar), it is equivalent to multiply and using numpy.multiply(a, b) or a * b is preferred. If a is a
numpy.matmul — NumPy v2.1 Manual
numpy.matmul# numpy.matmul(x1, x2, /, out=None, *, casting='same_kind', order='K', dtype=None, subok=True[, signature, axes, axis]) = <ufunc 'matmul'># Matrix product of two arrays. Parameters: x1, x2array_likeInput arrays, scalars not allowed. outndarray, optionalA location into which the result is stored. If provided, it must have a shape that matches the signature (n,k),(k,m)->(n,m). If not pro
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