We have covered a variety of classification models including logistic regression, k-nearest neighbors, decision trees, random forest, and naive bayes. In fact, we even implemented logistic regression from scratch. All of these models have their different strengths and weaknesses, which we have discussed. However, they should provide you with a good set of tools to start doing classification with Go.
In the next chapter, we will discuss yet another type of machine learning called clustering. This is the first unsupervised technique that we will discuss, and we will try a few different approaches.
