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  1. Reading 13 items
    All Textbooks used in our courses are all in the library or freely available on the web. Course leaders/lecturers will inform you which books are core and which are optional at the start of each term.
    1. Pattern Recognition and Machine Learning - Christopher M. Bishop 2006

      Book Recommended

    2. Bayesian Reasoning and Machine Learning - David Barber 2012

      Book Recommended

    3. Bayesian Reasoning and Machine Learning - David Barber 2012 (electronic resource)

      Book Recommended

    4. Time Series Analysis and its Applications: With R Examples - Robert H. Shumway, David S. Stoffer 2011

      Book Recommended

    5. Time Series Analysis and Its Applications: With R Examples - Robert H. Shumway, David S. Stoffer 2011

      Book Recommended

    6. Machine Learning - Tom M. Mitchell 1997

      Book Recommended

    7. Machine Learning - Tom M. Mitchell 2011

      Book Recommended

    8. Prediction, Learning, and Games - Nicolò Cesa-Bianchi, Gábor Lugosi 2006

      Book Further

    9. Prediction, Learning, and Games - Nicol Cesa-Bianchi, Gbor Lugosi 2006 (electronic book)

      Book Further

    10. Time Series Analysis by State Space Methods - J. Durbin, S. J. Koopman 2012 (electronic resource)

      Book Further

    11. Reinforcement Learning - Richard S. Sutton, Andrew G. Barto, Francis Bach 2018

      Book Recommended The 2018 edition is preferable, as the area is rapidly developing.

    12. Reinforcement Learning - Richard S. Sutton, Andrew G. Barto 1998

      Book Further

    13. Reinforcement Learning: Introduction - Richard S Sutton, Andrew G Barto 2012

      Book Further

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