training deep leaning models let' start with regularization we added small snippet of code within the train_network(function that computes the sum of absolute values of parameters and adds to the loss computed after multiplying with lambda (hyperparameterto enable regularizationwe would need to pass non-zero value to the lambda_l variable listing - demonstrates regularization for the network listing - regularization # regularization num_epochs batch_size weight_decay= #set to no reg lambda_l #enables regularization model neuralnetwork(loss_function nn bceloss(#binary crosss entropy loss adam_optimizer tch optim adam(model parameters(),lr ,weight_decay=weight_decay#define hyperparater for regularization #train network adam_loss train_network(model,adam_optimizer,loss_functionnum_epochs,batch_size,x_train,y_train,lambda_l =lambda_l #evaluate model evaluate_model(model,x_test,y_test,x_train,y_train,adam_loss