Titlebook: Neural Networks and Statistical Learning; Ke-Lin Du,M. N. S. Swamy Textbook 2019Latest edition Springer-Verlag London Ltd., part of Spring

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Ke-Lin Du,M. N. S. Swamyrward to characterize fibrous or membrane proteins owing to extreme difficulty in crystallization in the former, and insufficient spectral resolution due to sparing solubility or increased effective molecular m978-90-481-7100-2978-1-4020-4303-1

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Ke-Lin Du,M. N. S. Swamyrward to characterize fibrous or membrane proteins owing to extreme difficulty in crystallization in the former, and insufficient spectral resolution due to sparing solubility or increased effective molecular m978-90-481-7100-2978-1-4020-4303-1

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Ke-Lin Du,M. N. S. Swamyrward to characterize fibrous or membrane proteins owing to extreme difficulty in crystallization in the former, and insufficient spectral resolution due to sparing solubility or increased effective molecular m978-90-481-7100-2978-1-4020-4303-1

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yesian networks; and.? fuzzy sets and logic..Focusing on the prominent accomplishments and their practical aspects, this book provides academic and technical staff, as well as graduate students and researchers 978-1-4471-7454-7978-1-4471-7452-3

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Elements of Computational Learning Theory, are three concepts for deriving a generalization error bound for a trained machine. The fundamental theorem of learning theory relates PAC learnability, VC-dimension, and empirical risk-minimization principle. Another basic theorem in computational learning theory is no-free-lunch theorem. These to