A Few Useful Things to Know about Machine Learning.md

The paper presents some key lessons and "folk wisdom" that machine learning researchers and practitioners have learnt from experience and which are hard to find in textbooks. The fundamental goal of machine learning is to generalize beyond the training set. The data used to evaluate the model must be kept separate from the data used to learn the model. When we use generalization as a goal, we do not have access to a function that we can optimize. So we have to use training error as a proxy for test error.