What are some good but forgotten ideas in ML?

Is feature engineering still a thing? For example transforming circular images (like coins) to log-polar coordinates and maybe even taking the absolute value of Fourier transform to get rotation-invariant features.

Manifold learning is not very common anymore

I would also like to see a lot more probabilistic graphical models/ Bayesian networks.