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# Non-Negative Matrix Factorization

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The technique for extracting the important features of the data is
called *non-negative matrix factorization* (NMF).
This is one of the most sophisticated techniques covered in this book,
and it requires a bit more explanation and a quick introduction to
linear algebra. Everything you need to know will be covered in this
section.

To understand what NMF is doing, you’ll first need to understand a bit about matrix multiplication. If you’re already familiar with linear algebra, you can safely skip this section.

An example of matrix multiplication is shown in Figure 10-2.