How different machine learning models generalize?
Do you know how different machine learning models generalize? Maybe you know and understand the theory behind models like decision forests, neural networks, nearest neighbors, or SVMs. You might even have a good sense of which model works best for certain problems. But do you know how different machine learning models see the world and have you ever seen how they generalize differently?
