This lecture introduces the concept of neural network quantum states, focusing on parameterizing wave function amplitudes with neural networks. The instructor explains the use of complex valued functions, the importance of representing amplitudes with logs, and the process of training neural networks to minimize a loss function. The lecture also covers the application of neural network quantum states in solving complex spin models, exact sampling techniques, and comparisons with traditional methods in chemistry problems.