Deep Learning, Evaluation Metric, Loss Function, Data Science, Model Evaluation.
referred to a L2 loss. Source Pros Very intuitive and easy to understand (interpretable) Easily differentiable (due to presence of squared term) It has a convex curve — one global & local minima Cons Magnifies the error due to squared term Outliers get heavily penalized — not robust to outliers