
Categories  Download eBook: Neural Networks  
Book Catagory:Artificial Intelligence
In response to the exponentially increasing need to analyze vast amounts of data, this book provides scientists with a simple but systematic introduction to neural networks. Beginning with an introductory discussion on the role of neural networks in scientific data analysis, this book provides a solid foundation of basic neural network concepts. It contains an overview of neural network architectures for practical data analysis followed by extensive stepbystep coverage on linear networks, as well as, multilayer perceptron for nonlinear prediction and classification explaining all stages of processing and model development illustrated through practical examples and case studies. Later chapters present an extensive coverage on Self Organizing Maps for nonlinear data clustering, recurrent networks for linear nonlinear time series forecasting, and other network types suitable for scientific data analysis. With an easy to understand format using extensive graphical illustrations and multidisciplinary scientific context, this book fills the gap in the market for neural networks for multidimensional scientific data, and relates neural networks to statistics.
More Artificial Intelligence eBooks: Machine Learning, Neural and Statistical Classification A Gentle Guide to Constraint Logic Programming via ECLiPSe, 3rd Edition The LION Way: Machine Learning plus Intelligent Optimization From Bricks to Brains: The Embodied Cognitive Science of LEGO Robots A Course in Machine Learning Simply Logical: Intelligent Reasoning by Example Computers and Thought: A Practical Introduction to Artificial Intelligence Logic for Computer Science: Foundations of Automatic Theorem Proving Genetic Programming  New Approaches and Successful Applications Introduction to Computing: Explorations in Language, Logic, and Machines Computer Vision: Models, Learning, and Inference The Quest for Artificial Intelligence: A History of Ideas and Achievements Computational Linguistics: Models, Resources, Applications Artificial Intelligence: Foundations of Computational Agents Artificial Neural Networks  Methodological Advances and Biomedical Applications 
