MLVU 3.6: No free lunch
Channel: MLVU
Date: 2021-02-06

We end the lecture on a brief discussion about which model is best in general. Is there some method that we can always use to get a good result? Here, theory and general practice contradict one another. The no free lunch theorem tells us that there is no universal learning algorithm, but in practice we see that there is a semi-universal set of methods for choosing a model to fit to our data.

slides: https://mlvu.github.io/lecture03
lecturer: Peter Bloem