Hell, plain old linear regression is still going strong. The implication in the title of OP (that classical ML techniques are dying) is incorrect, though the body (that unsupervised learning is taking over from supervised learning) is spot-on.
Yes, linear regression is often quite good, especially if you have a good sense of what transformations you already need to do to the data to make linear regression work well. I think that many people unfortunately think that advanced techniques will somehow make up for deficient data (either poor quality data or too little data or both). Or worse, they think that advanced techniques will reduce the amount of thinking they have to do. Advanced techniques usually don't do either. Garbage in, garbage out as the saying goes. Simple techniques can often get good answers in much less time.
ISLR (aka "An Introduction to Statistical Learning: With Applications in R") is a great book on the principles of machine learning (including regression). And you get practical experience using R to actually implement such applications.
How beginner friendly do you think the book is? Asking as someone who's completely new to R (and data-related fields in general) who thinks the book might be interesting.
