In this chapter, we looked at various machine learning methods to do regression, clustering, and classification. We compared linear regression using machine learning tools with the same problem in Bayesian inference and standard OLS. Furthermore, we compared the results from the clustering machine learning algorithm, DBSCAN, with what we obtained for hierarchical clustering in Chapter 5 , Clustering. We concluded by looking at several classification algorithms available in Scikit-learn and how they performed on the same dataset.
With the UCI machine learning repository, finding practice data is not hard. I suggest you visit http://archive.ics.uci.edu/ml and look for a dataset to try any of the new things that we have gone through here.