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Reiss, Kristina [Editor]

Maschinelles Lernen : Modellierung von Lernen mit Maschinen ; mit 11 Tabellen

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Berlin; Heidelberg [u.a.]: Springer, 1992
Murphy, Kevin P. [Author]

Machine learning : a probabilistic perspective

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Cambridge, Massachusetts; London, England: The MIT Press, [2012]

Published in: Adaptive computation and machine learning series
Watanabe, Osamu [Editor] ; ALT 10 1999 Tokio

Algorithmic learning theory : 10th international conference ; proceedings

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Berlin; Heidelberg [u.a.]: Springer, 1999

Published in: Lecture notes in computer science ; 1720
Fischer, Paul [Editor] ; EuroCOLT 4 1999 Nordkirchen

Computational learning theory : 4th European conference ; proceedings

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Berlin; Heidelberg [u.a.]: Springer, 1999

Published in: Lecture notes in computer science ; 1572
Ben-David, Shai [Editor] ; EuroCOLT 3 1997 Yerûšālayim

Computational learning theory : third European conference, EuroCOLT '97, Jerusalem, Israel, March 17 - 19, 1997 ; proceedings

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Berlin [u.a.]: Springer, 1997

Published in: Lecture notes in computer science ; 1208
Cristianini, Nello [Author]; Shawe-Taylor, John [Author]

An introduction to support vector machines and other kernel-based learning methods - [1. publ., 11. print.]

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Cambridge [u.a.]: Cambridge Univ. Press, 2010
Skansi, Sandro [Author]

Introduction to deep learning : from logical calculus to artificial intelligence

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Cham, Switzerland: Springer, [2018]

Published in: Undergraduate topics in computer science
Rasmussen, Carl Edward [Author]; Williams, Christopher K. I. [Author]

Gaussian processes for machine learning

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Cambridge, Massachusetts; London, England: The MIT Press, [2006]

Published in: Adaptive computation and machine learning
Hastie, Trevor [Author]; Tibshirani, Robert [Author]; Wainwright, Martin J. [Author]

Statistical learning with sparsity : the lasso and generalizations

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Boca Raton [u.a.]: CRC Press, [2015]

Published in: Monographs on statistics and applied probability ; 143
Hastie, Trevor [Author]; Tibshirani, Robert [Author]; Friedman, Jerome H. [Author]

The elements of statistical learning : data mining, inference, and prediction

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New York; Berlin; Heidelberg [u.a.]: Springer, 2001

Published in: Springer series in statistics
James, Gareth [Author]; Witten, Daniela [Author]; Hastie, Trevor [Author]; Tibshirani, Robert [Author]

An introduction to statistical learning : with applications in R - [Corrected at 6th printing]

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New York; Heidelberg; Dordrecht; London: Springer, 2015

Published in: Springer texts in statistics
Frey, Brendan J. [Author]

Graphical models for machine learning and digital communication

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Cambridge, Mass. [u.a.]: MIT Press, 1998

Published in: Adaptive computation and machine learning- A Bradford book
Korstanje, Joos [Author]

Advanced forecasting with Python : with state-of-the-Art-Models including LSTMs, Facebook’s Prophet, and Amazon’s DeepAR

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Berkeley, CA: Apress, [2021]
Diederich, Joachim [Editor]

Artificial neural networks : concept learning

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Los Alamitos, Calif. [u.a.]: IEEE Computer Society Press, 1990

Published in: IEEE Computer Society neural networks technology series
Bolc, Leonard [Editor]; Bradshaw, Gary L. [Other]

Computational models of learning

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Berlin; Heidelberg [u.a.]: Springer, 1987

Published in: Symbolic computation ; Artificial intelligence
Cleeremans, Axel [Author]

Mechanisms of implicit learning : connectionist models of sequence processing

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Cambridge, Mass. [u.a.]: MIT Press, 1993

Published in: Neural network modeling and connectionism ; 5
López de Prado, Marcos M. [Author]

Advances in financial machine learning

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Hoboken, New Jersey: Wiley, [2018]
Hoyle, Rick H. [Editor]

Handbook of structural equation modeling - [Second edition]

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New York; London: The Guilford Press, [2023]
Koenig, Sven [Editor] ; SARA 5 2002 Kananaskis

Abstraction, reformulation, and approximation : 5th international symposium ; proceedings

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Berlin; Heidelberg: Springer, 2002

Published in: Lecture notes in computer science ; 2371
James, Gareth [Author]; Witten, Daniela [Author]; Hastie, Trevor [Author]; Tibshirani, Robert [Author]

An introduction to statistical learning : with applications in R - [Corrected at 8th printing]

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New York; Heidelberg; Dordrecht; London: Springer, [2017]

Published in: Springer texts in statistics

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