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  1. 1
    Semi-supervised learning /

    Semi-supervised learning /

    Published 2006
    Subjects: “…Supervised learning (Machine learning)…”
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  2. 2
    Introduction to machine learning /

    Introduction to machine learning / by Alpaydin, Ethem

    Published 2014
    Subjects: “…Machine learning.…”
    Full Text (via Skillsoft)
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  3. 3
    Machine learning from weak supervision : an empirical risk minimization approach /

    Machine learning from weak supervision : an empirical risk minimization approach / by Sugiyama, Masashi, 1974-, Bao, Han P., Ishida, Takashi, Lu, Nan, Sakayi, Tomoya, Niu, Gang

    Published 2022
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  4. 4
    Boosting : foundations and algorithms /

    Boosting : foundations and algorithms / by Schapire, Robert E.

    Published 2012
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  5. 5
    Boosting : foundations and algorithms /

    Boosting : foundations and algorithms / by Schapire, Robert E.

    Published 2012
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  6. 6
    Introduction to machine learning /

    Introduction to machine learning / by Alpaydin, Ethem

    Published 2014
    Subjects: “…Machine learning.…”
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  7. 7
    Machine learning in non-stationary environments : introduction to covariate shift adaptation /

    Machine learning in non-stationary environments : introduction to covariate shift adaptation / by Sugiyama, Masashi, 1974-

    Published 2012
    Subjects: “…Machine learning.…”
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  8. 8
    Deep learning /

    Deep learning / by Goodfellow, Ian, Bengio, Yoshua, Courville, Aaron

    Published 2016
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  9. 9
    Distributional reinforcement learning /

    Distributional reinforcement learning / by Bellemare, Marc G., Dabney, Will, Rowland, Mark (Research scientist)

    Published 2023
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  10. 10
    Semi-supervised learning /

    Semi-supervised learning /

    Published 2006
    Subjects: “…Supervised learning (Machine learning) http://id.loc.gov/authorities/subjects/sh94008290.…”
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  11. 11
    Boosting : foundations and algorithms /

    Boosting : foundations and algorithms / by Schapire, Robert E.

    Published 2012
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  12. 12
    Graphical models for machine learning and digital communication /

    Graphical models for machine learning and digital communication / by Frey, Brendan J.

    Published 1998
    Subjects: “…Machine learning.…”
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  13. 13
    Machine learning in non-stationary environments : introduction to covariate shift adaptation /

    Machine learning in non-stationary environments : introduction to covariate shift adaptation / by Sugiyama, Masashi, 1974-

    Published 2012
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  14. 14
    Introduction to machine learning /

    Introduction to machine learning / by Alpaydin, Ethem

    Published 2014
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  15. 15
    Introduction to machine learning /

    Introduction to machine learning / by Alpaydin, Ethem

    Published 2020
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  16. 16
    Machine learning : a probabilistic perspective /

    Machine learning : a probabilistic perspective / by Murphy, Kevin P., 1970-

    Published 2012
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  17. 17
    Gaussian processes for machine learning /

    Gaussian processes for machine learning / by Rasmussen, Carl Edward

    Published 2006
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  18. 18
    Learning with kernels : support vector machines, regularization, optimization, and beyond /

    Learning with kernels : support vector machines, regularization, optimization, and beyond / by Schölkopf, Bernhard

    Published 2002
    Subjects: “…Machine learning.…”
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  19. 19
    Gaussian processes for machine learning /

    Gaussian processes for machine learning / by Rasmussen, Carl Edward

    Published 2006
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  20. 20
    Introduction to machine learning /

    Introduction to machine learning / by Alpaydin, Ethem

    Published 2010
    Subjects: “…Machine learning. http://id.loc.gov/authorities/subjects/sh85079324.…”
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