In this chapter, you have learned the basics of unsupervised learning and using the k-means algorithm for clustering.
There are many clustering algorithms that show different behavior. Visualization is key when it comes to unsupervised learning algorithms, and you have seen a couple of different ways to visualize and inspect your dataset.
In the next chapter, you will learn other libraries which are commonly used with NumPy such as SciPy, Pandas and scikit-learn. These are all important libraries in the practitioner's toolkit, and they complement one another. You will find yourself using these libraries together with NumPy, as each will make certain tasks easier; hence, it's important to know more about the Python data science stack.