C SC 380

Syllabus:

Click here to view the course syllabus

Syllabus Updates:

• Click here updates to the syllabus as a result of the flood closure.

Neural Networks Resources on the Web:

• The Neural Networks FAQ: This is probably the largest repository of information on Neural Networks available on the web.
• SNNS: One of the best available neural networks simulation packages -- C++ based
• JNNS: A Java implementation of SNNS with a decent GUI.
• Flood: An open source Neural Networks C++ library
• Neural Lab: A neural networks simulation environment with a decent GUI

Class Overheads:

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• Introduction
• Learning Processes
• Chapter 1: Single Layer Perceptrons
• Chapter 2: Regression Models
• Chapter 3: Least Mean Squares Algorithm
• Chapter 4: Multilayer Perceptrons and Back Propagation
• Chapter 5: Kernel Methods and Radial Basis Function Networks
• Chapter 6: Support Vector Machines
• Chapter 7: Regularization Theory
• Committee Machines
• Chapter 8: Principal Component Analysis
• Chapter 9: Self Organizing Maps
• Chapter 10: Information Theoretic Models
• Chapter 11: Stochastic Machines
• Chapter 12: Dynamic Programming (Here is the link to the cell phone routing problem demo)
• Chapter 13: Neurodynamics and Temporal Processing

Assignments:

• Assignment 1: Basic Perceptrons (due: 1/21/2009)
• Assignment 2: Multilayer linear Perceptrons (due: 1/28/2009)
• Assignment 3: Background routines for back propagation (due: 2/11/2009)
• Assignment 4: RBF Mappings
• Assignment 5: Back propagation or Neural Networks package comparison