In this section, let's explain the Matrix Factorization Model (MF) and the Alternating Least Squares method. Before we get to know about the Matrix Factorization Model, we'll define the objective once again. Imagine we have ratings given to items by a number of users. Let's define the ratings given by users on items in a matrix form given by *R*, as shown in the following diagram:

In the preceding diagram, we observe that user Ted has rated items B and D as 4 and 3 respectively. In a collaborative filtering approach, the first step before generating recommendations is to fill the empty spaces, ...

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