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Neural Networks: Methodology and Applications
Neural Networks: Methodology and Applications by Gérard Dreyfus
Springer; Softcover reprint of hardcover 1st ed. 2005 edition (November 9, 2010) | ISBN: 3642061877 | PDF | 10.25 MB | 516 pages
Neural networks represent a powerful data processing technique that has reached maturity and broad application. When clearly understood and appropriately used, they are a mandatory component in the toolbox of any engineer who wants make the best use of the available data, in order to build models, make predictions, mine data, recognize shapes or signals, etc. Ranging from theoretical foundations to real-life applications, this book is intended to provide engineers and researchers with clear methodologies for taking advantage of neural networks in industrial, financial or banking applications, many instances of which are presented in the book. For the benefit of readers wishing to gain deeper knowledge of the topics, the book features appendices that provide theoretical details for greater insight, and algorithmic details for efficient programming and implementation. The chapters have been written by experts and edited to present a coherent and comprehensive, yet not redundant, practically oriented introduction.

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2001-06-13 12:10:13 by datamouse

An article in Rolling Stone (October 20, 1994) by Adam Miller called J. Philippe Rushton a 'professor of hate,' someone who 'takes money from an organization with a terrible past' (the Pioneer Fund, a foundation said to have an orientation toward eugenics). He is accused of being 'obsessed with intelligence and genetics' to the point of having 'racist' attitudes by Jeffrey Rosen and Charles Lane in The New Republic symposium on IQ (October 31, 1994). They single out Rushton for linking ethnocentricism to genetic factors; this in turn subjects him to the broad brush of being, along with Richard J. Herrnstein and Charles Murray, 'Neo-Nazis' Newsweek (October 24, 1994). In The Chronicle of Higher Education (October 26, 1994) critiquing Herrnstein and Murray's The Bell Curve it is clear...

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Solid understanding of the principles of Tick Data, Support Vector Machines, Neural Networks or similar. · Knowledge of machine learning an absolute plus. In Summary – We require ... Required for this is C++ / Matlab / R / S+ / with a Master's / MSc ...

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