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Data-Driven Computational Neuroscience: Machine Learning and Statistical Models

Bielza, Concha Concha Bielza, Pedro Larrañaga,

Verlag: Cambridge University Press, 2020

ISBN 10: 110849370X ISBN 13: 9781108493703

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Zustand: Very Good. Shipped within 24 hours from our UK warehouse. Clean, undamaged book with no damage to pages and minimal wear to the cover. Spine still tight, in very good condition. Remember if you are not happy, you are covered by our 100% money back guarantee. Bestandsnummer des Verk�ufers 6545-9781108493703

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Data-Driven Computational Neuroscience

Bielza, Concha; Larra�aga, Pedro

Verlag: Cambridge University Press, 2020

ISBN 10: 110849370X ISBN 13: 9781108493703

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Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide. Bestandsnummer des Verk�ufers ABNR-271379

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DATA-DRIVEN COMPUTATIONAL NEUROSCIENCE

CONCHA BIELZA , PEDRO LARRAñAGA

Verlag: Cambridge University Press, 2020

ISBN 10: 110849370X ISBN 13: 9781108493703

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Zustand: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. Bestandsnummer des Verk�ufers ABEJUNE24-323785

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Data-Driven Computational Neuroscience: Machine Learning and Statistical Models

Concha Bielza (Universidad Politecnica de Madrid)

Verlag: Cambridge University Press, United Kingdom, Cambridge, 2020

ISBN 10: 110849370X ISBN 13: 9781108493703

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Paperback. Zustand: Very Good. Data-driven computational neuroscience facilitates the transformation of data into insights into the structure and functions of the brain. This introduction for researchers and graduate students is the first in-depth, comprehensive treatment of statistical and machine learning methods for neuroscience. The methods are demonstrated through case studies of real problems to empower readers to build their own solutions. The book covers a wide variety of methods, including supervised classification with non-probabilistic models (nearest-neighbors, classification trees, rule induction, artificial neural networks and support vector machines) and probabilistic models (discriminant analysis, logistic regression and Bayesian network classifiers), meta-classifiers, multi-dimensional classifiers and feature subset selection methods. Other parts of the book are devoted to association discovery with probabilistic graphical models (Bayesian networks and Markov networks) and spatial statistics with point processes (complete spatial randomness and cluster, regular and Gibbs processes). Cellular, structural, functional, medical and behavioral neuroscience levels are considered. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged. Bestandsnummer des Verk�ufers GOR014300744

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