This lecture explores the spectral bias of polynomial neural networks, focusing on the analysis of Polynomial Networks (PNs) with multiplicative layers. It delves into the theoretical aspects of the Spectral Bias of Neural Networks, the NTK perspective, and the implications on learning different frequencies. The lecture also covers the experimental setup, results, and future directions for research.