Summary
In this chapter, the main clustering algorithms were discussed in detail. We implemented them (using scikit-learn) and compared the results. Also, the most relevant dimensionality reduction technique, principal component analysis, was presented and implemented. You should now have the knowledge to use the main unsupervised learning techniques in real scenarios using Python and its libraries.
In the next chapter, the supervised learning algorithms will be discussed, for both classification and regression problems.
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