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  1. 1
    Bioinformatics : the machine learning approach / Pierre Baldi, Søren Brunak.
    by Baldi, Pierre
    Published 2001
    Edition: 2nd ed.
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  2. 2
    Learning Bayesian networks / Richard E. Neapolitan.
    by Neapolitan, Richard E.
    Published 2004
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  3. 3
    Recurrent neural networks for prediction : learning algorithms, architectures, and stability / Danilo P. Mandic, Jonathon A. Chambers.
    by Mandic, Danilo P.
    Published 2001
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  4. 4
    International journal of computational intelligence & applications
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  5. 5
    Learning from data : concepts, theory, and methods / Vladimir Cherkassky, Filip Mulier.
    by Cherkassky, Vladimir S.
    Published 2007
    Edition: 2nd ed.
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  6. 6
    Bayesian networks and decision graphs / Finn V. Jensen, Thomas D. Nielsen.
    by Jensen, Finn V.
    Published 2007
    Edition: 2nd ed.
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  7. 7
    Learning and generalisation : with applications to neural networks / M. Vidyasagar.
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  8. 8
    An introduction to computational learning theory Michael J. Kearns, Umesh V. Vazirani.
    by Kearns, Michael J.
    Published 1994
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  9. 9
    Bioinformatics the machine learning approach / Pierre Baldi, Sren Brunak.
    by Baldi, Pierre
    Published 2001
    Edition: 2nd ed.
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  10. 10
    Deep learning using MATLAB : neural network applications / K. Taylor.
    by Taylor, K.
    Published 2017
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  11. 11
    Intelligence emerging : adaptivity and search in evolving neural systems / Keith L. Downing.
    by Downing, Keith L.
    Published 2015
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  12. 12
    Intelligence emerging adaptivity and search in evolving neural systems / Keith L. Downing.
    by Downing, Keith L.
    Published 2015
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  13. 13
    Introduction to deep learning : from logical calculus to artificial intelligence / Sandro Skansi.
    by Skansi, Sandro
    Published 2018
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  14. 14
    MATLAB deep learning : with machine learning, neural networks and artificial intelligence / Phil Kim.
    by Kim, Phil (programmer)
    Published 2017
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  15. 15
    Learning from data concepts, theory, and methods / Vladimir Cherkassky and Filip Mulier.
    by Cherkassky, Vladimir
    Published 2007
    Edition: 2nd ed.
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  16. 16
    Artificial intelligence and machine learning for business : a no-nonsense guide to data driven technologies / Steven Finlay.
    by Finlay, Steven, 1969-
    Published 2018
    Edition: Third edition.
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  17. 17
    Advanced deep learning with Keras : apply deep learning techniques, autoencoders, GANs, variational autoencoders, deep reinforcement learning, policy gradients, and more / Rowel Atienza.
    by Atienza, Rowel
    Published 2018
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  18. 18
    Generative adversarial networks projects : build next-generation generative models using TensorFlow and Keras / Kailash Ahirwar.
    by Ahirwar, Kailash
    Published 2019
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  19. 19
    Advanced deep learning with keras apply deep learning techniques, autoencoders, GANs, variational autoencoders, deep reinforcement learning, policy gradients, and more / Rowel Atienza.
    by Atienza, Rowel
    Published 2018
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  20. 20
    Grokking deep learning / Andrew W. Trask.
    by Trask, Andrew W.
    Published 2019
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