Chapter 4. Advanced Features

In the previous chapters we have studied several algorithms for very different tasks, from classification and regression to clustering and dimensionality reduction. We showed how we can apply these algorithms to predict results when faced with new data. That is what machine learning is all about. In this last chapter, we want to show some important concepts and methods you should take into account if you want to do real-world machine learning.

  • In real-world problems, usually data is not already expressed by attribute/float value pairs, but through more complex structures or is not structured at all. We will learn feature extraction techniques that will allow us to extract scikit-learn features from data.
  • From the initial ...

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