Neural Network L1 Regularization Using Python -- Visual Studio Magazine

The data science doctor continues his exploration of techniques used to reduce the likelihood of model overfitting, caused by training a neural network for too many iterations. Regularization is a technique used to reduce the likelihood of neural network model overfitting. Model overfitting can occur when you train a neural network for too many iterations. This sometimes results in a situation where the trained neural network model predicts the output values for the training data very well, with little error and high accuracy, but when the trained model is applied to new, previously unseen data, the model predicts poorly. There are several forms of regularization.