A complete course in data collection and analysis for students who need to go beyond the basics. A true course companion, the engaging writing style takes readers through challenging topics, blending examples and exercises with careful explanations and custom-drawn figures ensuring the most daunting concepts can be fully understood.
Neural Networks have influenced many areas of research but have only just started to be utilized in social science research. Neural Networks provides the first accessible introduction to this analysis as a powerful method for social scientists. It provides numerous studies and examples that illustrate the advantages of neural network analysis over other quantitative and modeling methods in wide spread use among social scientists. The author presents the methods in an accessible style for the reader who does not have a background in computer science. Features include an introduction to the vocabulary and framework of neural networks, a concise history of neural network methods, a substantial review of the literature, detailed neural network applications in the social sciences, coverage of the most common alternative neural network models, methodological considerations in applying neural networks, examples using the two leading software packages for neural network analysis, and numerous illustrations and diagrams."--Pub. desc.
A complete course in data collection and analysis for students who need to go beyond the basics. A true course companion, the engaging writing style takes readers through challenging topics, blending examples and exercises with careful explanations and custom-drawn figures ensuring the most daunting concepts can be fully understood.
Neural Networks have influenced many areas of research but have only just started to be utilized in social science research. Neural Networks provides the first accessible introduction to this analysis as a powerful method for social scientists. It provides numerous studies and examples that illustrate the advantages of neural network analysis over other quantitative and modeling methods in wide spread use among social scientists. The author presents the methods in an accessible style for the reader who does not have a background in computer science. Features include an introduction to the vocabulary and framework of neural networks, a concise history of neural network methods, a substantial review of the literature, detailed neural network applications in the social sciences, coverage of the most common alternative neural network models, methodological considerations in applying neural networks, examples using the two leading software packages for neural network analysis, and numerous illustrations and diagrams."--Pub. desc.
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