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21 - 30 of 70 search results for Economics Syllabus |u:mlg.eng.cam.ac.uk where 7 match all words and 63 match some words.
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  2. Addressing Climate Change

    https://mlg.eng.cam.ac.uk/carl/climate/eaccs.html
    21 May 2024: Membership immediately creates economic pressure to cut emissions (for all members, not just large emitters).
  3. Machine Learning 4f13 Lent 2013

    https://mlg.eng.cam.ac.uk/teaching/4f13/1213/
    19 Nov 2023: LECTURE SYLLABUS. This year, the exposition of the material will be centered around three specific machine learning areas: 1) supervised non-paramtric probabilistic inference using Gaussian processes, 2) the TrueSkill ranking
  4. Machine Learning 4f13 Lent 2008

    https://mlg.eng.cam.ac.uk/teaching/4f13/0708/
    19 Nov 2023: LECTURE SYLLABUS. Jan 18 . Introduction to Machine Learning(1L): review of probabilistic models, relation to coding terminology: Bayes rule, supervised, unsupervised and reinforcement learning.
  5. 13 Feb 2023: 1978). He-donic prices and the demand for clean air.Journal of Environmental Economics & Man-agement, 5, 81–102.
  6. Machine Learning 4f13 Lent 2009

    https://mlg.eng.cam.ac.uk/teaching/4f13/0809/
    19 Nov 2023: LECTURE SYLLABUS. Jan 16 . Introduction to Machine Learning(1L): review of probabilistic models, relation to coding terminology: Bayes rule, supervised, unsupervised and reinforcement learning.
  7. Machine Learning 4f13 Lent 2012

    https://mlg.eng.cam.ac.uk/teaching/4f13/1112/
    19 Nov 2023: LECTURE SYLLABUS. This year, the exposition of the material will be centered around three specific machine learning areas: 1) supervised non-paramtric probabilistic inference using Gaussian processes, 2) the latent Dirichlet
  8. nips2007-final.dvi

    https://mlg.eng.cam.ac.uk/pub/pdf/SilChuGha08.pdf
    13 Feb 2023: This setup is very closely related to the classicseemingly unrelated regressionmodel popular in economics [12].
  9. Machine Learning 4f13 Lent 2011

    https://mlg.eng.cam.ac.uk/teaching/4f13/1011/
    19 Nov 2023: LECTURE SYLLABUS. Jan 20 . Introduction to Machine Learning(1L): review of probabilistic models, relation to coding terminology: Bayes rule, supervised, unsupervised and reinforcement learning.
  10. Machine Learning 4f13 Lent 2010

    https://mlg.eng.cam.ac.uk/teaching/4f13/0910/
    19 Nov 2023: LECTURE SYLLABUS. Jan 14 . Introduction to Machine Learning(1L): review of probabilistic models, relation to coding terminology: Bayes rule, supervised, unsupervised and reinforcement learning.
  11. Machine Learning 4f13 Michaelmas 2015

    https://mlg.eng.cam.ac.uk/teaching/4f13/1516/
    19 Nov 2023: LECTURE SYLLABUS. This year, the exposition of the material will be centered around three specific machine learning areas: 1) supervised non-parametric probabilistic inference using Gaussian processes, 2) the TrueSkill ranking

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