  The scope of this teaching package is to make a brief induction to Artificial
Neural Networks (ANNs) for people who have no previous knowledge of them. We
first make a brief introduction to models of networks, for then describing in
general terms ANNs. As an application, we explain the backpropagation
algorithm, since it is widely used and many other algorithms are derived from
it. The user should know algebra and the handling of functions and vectors.
Differential calculus is recommendable, but not necessary. The contents of this
package should be understood by people with high school education. It would be
useful for people who are just curious about what are ANNs, or for people who
want to become familiar with them, so when they study them more fully, they
will already have clear notions of ANNs. Also, people who only want to apply
the backpropagation algorithm without a detailed and formal explanation of it
will find this material useful. This work should not be seen as "Nets for
dummies", but of course it is not a treatise. Much of the formality is skipped
for the sake of simplicity. Detailed explanations and demonstrations can be
found in the referred readings. The included exercises complement the
understanding of the theory. The on-line resources are highly recommended for
extending this brief induction.
