1. What is an artificial neural network and for what types of problems can it be used?

2. Compare artificial and biological neural networks. What aspects of biological networks are not mimicked by artificial ones? What aspects are similar?

3. What are the most common ANN architectures? For what types of problems can they be used?

4. ANN can be used for both supervised and unsupervised learning. Explain how they learn in a supervised mode and in an unsupervised mode.

5. What are SVM? How do they work?

Hands-On Exercises

1. Go to the Teradata University Network Web site (teradatauniversitynetwork.com) or a URL given by your instructor. Locate Web seminars related to data mining and neural networks. Specifically, view the seminar given by Professor Hugh Watson at the SPIRIT2005 conference at Oklahoma State University; then, answer the following questions:

a. Which real-time application at Continental Airlines might have used a neural network?

b. What inputs and outputs can be used in building a neural network application?

c. Given that its data mining applications are in real time, how might Continental implement a neural network in practice?

d. What other neural network applications would you propose for the airline industry?

need elobrated answer to each question with no plagrism