L1 Regularization, L2 Regularization, Regularization, Early Stopping, Dropout.
weights to the loss function. This tends to evenly distribute the importance across all features, reducing the magnitude of weights and preventing them from growing too large. 2. Dropout Dropout is a popular regularization technique specifically designed for neural networks. During training,