AIP Conference Proceedings 151 on Neural Networks for Computing
AIP Conference Proceedings 151 on Neural Networks for Computing
Explorations in parallel distributed processing: a handbook of models, programs, and exercises
Explorations in parallel distributed processing: a handbook of models, programs, and exercises
Twelve-product wrap-up: neural networks
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Neurocomputing: foundations of research
Neurocomputing: foundations of research
Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Biologically based machine learning paradigms: an introductory course
SIGCSE '92 Proceedings of the twenty-third SIGCSE technical symposium on Computer science education
A first undergraduate course in neural networks
SIGCSE '90 Proceedings of the twenty-first SIGCSE technical symposium on Computer science education
Teaching neural networks using LEGO handy board robots in an artificial intelligence course
SIGCSE '03 Proceedings of the 34th SIGCSE technical symposium on Computer science education
An intelligent agent approach for teaching neural networks using LEGO® handy board robots
Journal on Educational Resources in Computing (JERIC) - Special issue on robotics in undergraduate education. Part 2
Cluster-based under-sampling approaches for imbalanced data distributions
Expert Systems with Applications: An International Journal
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Neural networks have been called “more important than the atomic bomb” and have received a major funding commitment from DARPA. Nevertheless, it is difficult to find even a mention of neural network concepts and applications in many computer science or information systems curricula. In fact, few computer science or information systems faculty are aware of the profound implications of neurocomputing on the future of their field. This paper contends that neural networks must be a significant part of any artificial intelligence course. It illustrates how neural network concepts can be integrated into traditional artificial intelligence course material. Two programming packages for simulating neural networks on personal computers are recommended.