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that the reader does not come away with the impression that backpropagation has a monopoly here.The final chapter tries to make sense of the seemingly disparate collection of objects that populate the neural network universe by introducing a series of taxonomies for network architectures,neuron types and algorithms.It also places the study of nets in the general context of that of artificial intelligence and closes with a brief history of its research. The usual provisos about the range of material covered and introductory texts apply,it is neither possible nor desirable to be exhaustive in a work of this nature. However,most of the major network types have been dealt with and,while there are a plethora of training algorithms that might have been included (but weren't)I believe that an understanding of those presented here should give the reader a firm foundation for understanding others they may encounter elsewhere. 11that the reader does not come away with the impression that backpropagation has a monopoly here. The final chapter tries to make sense of the seemingly disparate collection of objects that populate the neural network universe by introducing a series of taxonomies for network architectures, neuron types and algorithms. It also places the study of nets in the general context of that of artificial intelligence and closes with a brief history of its research. The usual provisos about the range of material covered and introductory texts apply; it is neither possible nor desirable to be exhaustive in a work of this nature. However, most of the major network types have been dealt with and, while there are a plethora of training algorithms that might have been included (but weren't) I believe that an understanding of those presented here should give the reader a firm foundation for understanding others they may encounter elsewhere. 11
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