Database Reference
In-Depth Information
Summary
In this chapter, we explored two new unsupervised learning methods, PCA and SVD, for
dimensionality reduction. We saw how to extract features for and train these models using
facial image data. We visualized the results of the model in the form of Eigenfaces, saw
how to apply the models to transform our original data into a reduced dimensionality rep-
resentation, and investigated the close link between PCA and SVD.
In the next chapter, we will delve more deeply into techniques for text processing and ana-
lysis with Spark.
