Interactions between predictive analytics, ML, and case-based and rules-based reasoning
Personally, I'm not that enamored of the "rules-based reasoning vs case-based reasoning" categorizatin; I'm not sure it is a particularly useful mindset for modern machine learning.  For instance, deep learning is one of the most effective ML methods used today in several domains, yet it doesn't seem to fall into either of those categories.  That's just my opinion; perhaps others might find it useful.

Rather than trying to find this kind of high-level generalization about how ML works, I think it might be more useful to study some specific ML techniques: linear regression, k-nearest neighbors, SVM, random forest, deep learning, etc.