This lecture covers the statistical view of artificial neural networks, focusing on generative models, likelihood of data, and statistical interpretation. It discusses the use of sigmoidal and softmax units for classification tasks, cross-entropy loss functions, and the interpretation of outputs as probabilities. A quiz at the end tests understanding of these concepts.