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This course explores the organization of synaptic connectivity as the basis of neural computation and learning.
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English
English [CC]
FREE
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Description
Perceptrons and dynamical theories of recurrent networks including amplifiers, attractors, and hybrid computation are covered. Additional topics include backpropagation and Hebbian learning, as well as models of perception, motor control, memory, and neural development.
Course content
- From Spikes to Rates Unlimited
- Lateral Inhibition and Feature Selectivity Unlimited
- Hamiltonian Dynamics Unlimited
- Antisymmetric Networks Unlimited
- Excitatory-Inhibitory Networks Unlimited
- VQ Unlimited
- PCA Unlimited
- Delta Rule Unlimited
- Conditioning Unlimited
- Backpropagation Unlimited
- More Backpropagation Unlimited
Instructor
Massachusetts Institute of Technology
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