My understanding is that regularization will generally help prediction tasks. What about for situations where we want to conduct a study to understand the effect of a specific predictor on the dependent variable? Is it fair to say that we should use multiple regression instead of something like ridge in this case since the multiple regression coefficients aren't biased?
Correct me if I'm wrong, but I think what I'm basically trying to ask if there is any place for Ridge Regression in inference tasks?