Machine Learning, Regularization, Machine Learning Concept, Learning, Learning Journey.
Why do we prefer smaller coefficients over large ones? How do large coefficients equate to increased model complexity? Why there are multiple combinations of weights and biases in a neural network? Why aren’t bias terms penalized in L1 and L2 regularization? What is regularization? Why we need it?