Machine Learning, Regularization, Machine Learning Concept, Learning, Learning Journey.
not to others like sigmoid or tanh). This phenomenon is referred to as ‘scale symmetry’ in neural networks. I’ve been reading about L1 and L2 regularization and observed that the penalty terms mainly focus on weights rather than biases. But why is that? Aren’t biases also coefficients that could be