Machine Learning, Generalization, Regularization, Overfitting, Bias.
Bias Bias is defined as the average squared difference between predictions and true values. It’s a measure of how good your model fits the data. Zero bias would mean that the model captures the true data generating process perfectly. Both your training and validation loss would go to zero. That is