Deep Learning, Machine Learning, Python, TensorFlow, Artificial Intelligence.
switches from behaving quadratically (like squared loss) to linearly (like the absolute loss). The benefit of Huber Loss is that it is less sensitive to outliers compared to MSE loss. By having a smooth transition from squared loss to absolute loss, it balances between robustness to outliers and