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9.641J Introduction to Neural Networks (MIT) 9.641J Introduction to Neural Networks (MIT)

Description

Organization of synaptic connectivity as the basis of neural computation and learning. Single and multilayer perceptrons. Dynamical theories of recurrent networks: amplifiers, attractors, and hybrid computation. Backpropagation and Hebbian learning. Models of perception, motor control, memory, and neural development. Organization of synaptic connectivity as the basis of neural computation and learning. Single and multilayer perceptrons. Dynamical theories of recurrent networks: amplifiers, attractors, and hybrid computation. Backpropagation and Hebbian learning. Models of perception, motor control, memory, and neural development.

Subjects

synaptic connectivity | synaptic connectivity | computation | computation | learning | learning | multilayer perceptrons | multilayer perceptrons | recurrent networks | recurrent networks | amplifiers | amplifiers | attractors | attractors | hybrid computation | hybrid computation | Backpropagation | Backpropagation | Hebbian learning | Hebbian learning | perception | perception | motor control | motor control | memory | memory | neural development | neural development | 9.641 | 9.641 | 8.594 | 8.594

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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9.641J Introduction to Neural Networks (MIT)

Description

Organization of synaptic connectivity as the basis of neural computation and learning. Single and multilayer perceptrons. Dynamical theories of recurrent networks: amplifiers, attractors, and hybrid computation. Backpropagation and Hebbian learning. Models of perception, motor control, memory, and neural development.

Subjects

synaptic connectivity | computation | learning | multilayer perceptrons | recurrent networks | amplifiers | attractors | hybrid computation | Backpropagation | Hebbian learning | perception | motor control | memory | neural development | 9.641 | 8.594

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

Site sourced from

https://ocw.mit.edu/rss/all/mit-allarchivedcourses.xml

Attribution

Click to get HTML | Click to get attribution | Click to get URL

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