Neural Networks

Regularization

Change L1, L2 and early stopping while watching validation loss.

Epoch 0 / 2000

Loss = mean ½(prediction − target)²Press Train step to calculate the first training update.

60 training and 20 validation points. Inverted dropout applies a seeded mask during training; the network above shows inference, with all units enabled. Each step is one mini-batch update. Numerical work runs in a worker.

Opening this lab…

No account required. Local images and model files stay in your browser. Educational models demonstrate mechanisms; they are not production predictors.

Regularization

Continue exploring