KOBI

The second half of this course covers basic theoretical approaches to neural networks, their activity and dynamic states, and their capacity for learning through activity-dependent plasticity. In addition, the course introduces contemporary theories of behavioural conditioning and reinforcement learning as well as a number of abstract approaches to representational learning (expectation maximization, principal components analysis, etc).

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