Summary

In this chapter, our focus was on feature extraction techniques. We explored how we can use dimensionality reduction techniques and autoencoders to reduce the number of features in order to make machine learning models more effective.

However, numerical and image data are only two examples of data. In the next chapter, we continue with the feature engineering methods, but for textual data, which is more common in contemporary software engineering.