In this chapter, we have trained and evaluated various unsupervised machine learning models and techniques in Apache Spark using a variety of real-world use cases, including partitioning the various substances found in the human brain using image segmentation and helping to develop a movie recommendation system by reducing the dimensionality of a high-dimensional user-community movie ratings dataset.
In the next chapter, we will develop, test, and evaluate some common algorithms that are used in natural language processing (NLP) in an attempt to train machines to automatically analyze and understand human text and speech!
