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  2. Machine Learning 4f13 Lent 2014

    https://mlg.eng.cam.ac.uk/teaching/4f13/1314/
    19 Nov 2023: There is no final exam. Time: 9:00 - 10:00 Mondays and 9:00 - 10:00 Thursdays.
  3. Machine Learning 4f13 Lent 2015

    https://mlg.eng.cam.ac.uk/teaching/4f13/1415/
    19 Nov 2023: There is no final exam. Time: 9:00 - 10:00 Mondays and 9:00 - 10:00 Thursdays.
  4. Probabilistic Machine Learning 4f13 Michaelmas 2016

    https://mlg.eng.cam.ac.uk/teaching/4f13/1617/
    19 Nov 2023: There is no final exam. Time: 8 double lectures on Fridays at 14:00 - 16:00.
  5. Probabilistic Machine Learning 4f13 Michaelmas 2021

    https://mlg.eng.cam.ac.uk/teaching/4f13/2122/
    19 Nov 2023: There is no final exam. Format:This year the course will be delivered entirely online.
  6. Cambridge Machine Learning Group Publications

    https://mlg.eng.cam.ac.uk/pub/authors/
    13 Feb 2023: Publications, Machine Learning Group, Department of Engineering, Cambridge. current group:. [former members:. [by year:. [Tameem Adel. George Nicholson, Marta Blangiardo, Mark Briers, Peter J Diggle, Tor Erlend Fjelde, Hong Ge, Robert J B Goudie,
  7. Topics for Machine Learning Quals

    https://mlg.eng.cam.ac.uk/zoubin/topics-list.html
    27 Jan 2023: Topics for Machine Learning Quals. Foundations. Shannon's Source Coding Theorem. Bayes Rule. Dutch Books. Cox Axioms. Bayesian model comparison. Models. Factor Analysis / PCA. Independent Components Analysis (ICA). Mixture models / k-means. Hidden
  8. 13 Feb 2023: Our analysis highlights global partnerships (SDG 17) as a pivot in global sustainability efforts, which have been strongly linked to economic growth (SDG 8). ... However, if economic growth and trade expansion were repositioned as a means instead of an
  9. Machine Learning Group Publications

    https://mlg.eng.cam.ac.uk/pub/topics/
    13 Feb 2023: Publications, Machine Learning Group, Department of Engineering, Cambridge. current group:. [former members:. [by year:. [Gaussian Processes and Kernel Methods. Gaussian processes are non-parametric distributions useful for doing Bayesian inference
  10. 4F13 Probabilistic Machine Learning: Coursework #1: Gaussian…

    https://mlg.eng.cam.ac.uk/teaching/4f13/1617/cw/coursework1.pdf
    19 Nov 2023: This data has 2-D input and scalar output. Visualise the data, for exam-ple using mesh(reshape(x(:,1),11,11),reshape(x(:,2),11,11),reshape(y,11,11));
  11. 4F13 Machine Learning: Coursework #1: Gaussian Processes Zoubin…

    https://mlg.eng.cam.ac.uk/teaching/4f13/1516/cw/coursework1.pdf
    19 Nov 2023: This data has 2-D input and scalar output. Visualise the data, for exam-ple using mesh(reshape(x(:,1),11,11),reshape(x(:,2),11,11),reshape(y,11,11));

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