Some resources and hints for those that wish to learn more about elementary AI subjects.
Subjects covered here:
(Artificial) Neural Net(work)s
(Artificial) Neural Net(work)s (NNs / ANNs)
The frequently suggested material is the ANN chapter of Mitchell's book "Machine Learning".
This book is unfortunately not published online but Barber's "Machine Learning, a Probabilistic Approach" (http://www.idiap.ch/~barber/mlgm.pdf) and Nilsson's "An introduction to Machine Learning" (http://ai.stanford.edu/~nilsson/mlbook.html) are and both cover the topic.
It is highly suggested that you read those chapters first (and for a greater understanding, the preceding chapters in Barber).
A smaller tutorial which also explains what ANNs does, graphically, can be found at
http://www.willamette.edu/~gorr/classes/cs449/Classification/perceptron.html
