Credit points: 3.0
Neural networks as computation models. The perception. Separability of data points. Realization of Boolean functions by multi-layer networks. Classification. VC dimension and the generalization problem. SVM and SVR. Approximating continuous functions by neural networks. Learning and data storage methods. Associative memories: storage capacity and dynamics.
Neural networks as computation models. The perception. Separability of data points. Realization of Boolean functions by multi-layer networks. Classification. VC dimension and the generalization problem. SVM and SVR. Approximating continuous functions by neural networks. Learning and data storage methods. Associative memories: storage capacity and dynamics.