Neurocomputers and Deep Learning

Course content

Various aspects of neurocomputers emphasizing deep learning approaches. Brainlike computing, characteristics of neurocomputers. Deterministic, probabilistic and spiking neuron models. Feed forward and recurrent neural networks. Deep structures of feed forward and recurrent neural networks. Deep learning: supervised and unsupervised machine learning algorithms for various deep neural networks. Neuromorphic chips.