Artificial Intelligence: Neural Networks Simplified
Indranarain Ramlall · SSRN Electronic Journal · 2009
Now standing as a major paradigm for data mining applications, Neural Networks have been widely used in many fields due to its ability to capture complex patterns present in the data. Under its feature extractor capability, Neural Networks extrapolate past pattern into future ones and thereby relieves the burden of having recourse to complex detection algorithm in case of pattern recognition such as face detection or fingerprint detection. The development of Neural Networks has been so rapid that they are now referred as the sixth generation of computing. While the main strength of Neural Networks is embedded in its non-linearity and data-driven aspects, its main shortcoming relates to the lack of explanation power in the trained networks due to the complex structure of the networks. This paper explains the distinct mechanisms embodied in Neural Networks, its strengths, weaknesses and applications.