This lecture focuses on the statistical interpretation of artificial neural networks, deriving the cross-entropy error function in the context of the likelihood of data under a neural network model. It covers the generation of predicted labels, the likelihood of input-output pairs, and the maximum likelihood for neural networks by minimizing the negative log-likelihood.