Neural Networks
Instructional
Material
Session by: Yash Gad
(yashgad@uiuc.edu)
Grade Level: 9 – 12,
undergraduate
Subjects: Applied
Mathematics – Matrix Algebra
Biology – Neuroscience
All materials (lesson plans,
this handout, and the powerpoint
presentation) are available for download at:
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Courses >
Neural Networks: Instructional Material
Topics
|
Lesson I Introduction to Neural Networks An Application of Matrix Multiplication An introduction
to neural network modeling, focusing primarily on the representation of neural
systems using matrix algebra. Lesson II Neural Network Structures Lateral Inhibition A look at
one of the most fundamental and commonly seen neural computations involving
groups of neurons in a network.
| Lesson III Neural Network Learning Hopfield Networks Analysis of a learning rule
in neural networks, by which neurons learn to strengthen their connections
based on correlated activities. Lesson IV Neural Network Learning Delta Rule Exploration
of the Delta Rule, a form of learning which is driven by errors in the output. |