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Identifying latent features

Print original_df and user_matrix using the console. The user_matrix is one of the factors of the original_df. Based on the values in the first column of the user_matrix, what do you think the latent feature may be summarizing?

Note the first row of user_matrix corresponds to User 1, the second row to User_2, and so on. Remember that latent features tend to represent underlying trends in the data and give items with these underlying trends similar scores.

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Building Recommendation Engines in Python

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