Goals
	• Understand – the perceptron, the basic unit of ANN computation (like transistor is to circuits), – the perceptron learning rule, – the class of functions a perceptron can represent, – multilayer feed-forward networks, – the back-propogation learning algorithm, and – the momentum variant of back-propogation. • Experience the strengths/weaknesses of multilayer feed-forward methods through experimentation.