Shallow learning algos

The Machine Learning specilization covers a few shallow learning algos. I am aware there are many more. Which ones are still relevant today and worth me learning?

Consider taking Deep Learning Specialization.

Sorry, I did not see your response. I was thinking more of things like k-nearest neighbours and naive bayes, not covered in the ML specialization. Are they still relevant today and worth devoting time to over NNs?

The 3rd course of MLS covered the K-Means algorithm but I don’t know about the k-nearest neighbours.

This is covered in the first course of NLP. But I don’t like it :full_moon_with_face: :confused:.