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  2. Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2021-22 …

    https://teaching21-22.eng.cam.ac.uk/content/engineering-tripos-part-iib-4g3-computational-neuroscience-2021-22
    describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in
  3. Computational and Biological Learning Lab

    https://cbl.eng.cam.ac.uk/vacancies/blg-phd/
    9 Jul 2024: Students in computational neuroscience benefit from the strong machine learning group within CBL. ... Students seeking to combine work in neuroscience and machine learning are particularly encouraged to apply.
  4. Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2020-21 …

    https://teaching21-22.eng.cam.ac.uk/content/engineering-tripos-part-iib-4g3-computational-neuroscience-2020-21
    describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in
  5. Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2018-19 …

    https://teaching21-22.eng.cam.ac.uk/content/engineering-tripos-part-iib-4g3-computational-neuroscience-2018-19
    describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in
  6. Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2017-18 …

    https://teaching21-22.eng.cam.ac.uk/content/engineering-tripos-part-iib-4g3-computational-neuroscience-2017-18
    describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in
  7. Engineering Tripos Part IIB, 4G3: Computational Neuroscience, 2019-20 …

    https://teaching21-22.eng.cam.ac.uk/content/engineering-tripos-part-iib-4g3-computational-neuroscience-2019-20
    describe models of plasticity and learning and how they apply to the basic paradigms of machine learning (supervised, unsupervised, reinforcement) as well as pattern formation in the nervous system. ... Content. The course covers basic topics in
  8. Engineering Tripos, Part IIB: Notice concerning Engineering Areas…

    https://teaching22-23.eng.cam.ac.uk/content/engineering-tripos-part-iib-notice-concerning-engineering-areas-2022-23
    Climate Change Mitigation. 4M23. Electricity and Environment (TPE22). 4M24. Computational Statistics and Machine Learning. ... 4M24. Computational Statistics and Machine Learning. Advice. Intending Civil Engineers are advised to study the broadest
  9. standalone.dvi

    https://mlg.eng.cam.ac.uk/pub/pdf/QuiRasWil07.pdf
    13 Feb 2023: A host of approximation techniques have recently been pro-posed to allow application of GPs to large problems in machine learning. ... However, learning good values of thehyperparameters is crucial, and it might come at a high computational cost
  10. 27 Jan 2023: Reader in Machine Learning, Oct 2003–Jan 2006Gatsby Computational Neuroscience Unit, University College London, UK. ... USA, 2007)Machine Learning Summer School (Tübingen, Germany, 2007)Machine Learning Summer School (Chicago, USA, 2005)Machine
  11. Engineering Tripos, Part IIB: Notice concerning Engineering Areas…

    https://teaching19-20.eng.cam.ac.uk/content/engineering-tripos-part-iib-notice-concerning-engineering-areas-2019-20
    Deep Learning and Structured data. 4F12. Computer Vision. 4F13. Probabilistic Machine Learning. ... 4F12. Computer vision. 4F13. Probabilistic Machine learning. 4M20. Robotics. 4M21. Software Engineering and Design.

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