1. Review of k-means clustering
Congratulations! You have completed the first of four chapters in the Unsupervised Learning in R course.
2. Chapter review
You have covered much in a short period. As a review:
You have learned the difference between supervised and unsupervised learning and about the two major goals of unsupervised learning, you have successfully created several k-means cluster models in R, gained intuition about how the k-means algorithm works, learned how to use model selection to handle the circumstance where the number of subgroups is not known beforehand, and finally, you performed clustering to gain insights on a fun real-world dataset.
3. Coming up: chapter 2
Coming up in Chapter 2, I will cover hierarchical clustering, which is a clustering method that is used when the number of clusters is not provided a priori.
4. Coming up: chapter 3
In Chapter 3, you will learn about principal components analysis, a method for doing dimensionality reduction.
5. Coming up: chapter 4
And finally in Chapter 4 you will apply everything you learned in the first three chapters to a data set covering breast cancer tumor observations. This will reinforce your learning from the earlier chapters and help you apply these skills to your own datasets.
6. See you in the next chapter!
See you in the next chapter.