Machine learning - Bayesian learning part 2

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Continuation of Bayesian learning for linear regression.
Course taught in 2013 at UBC by Nando de Freitas
  1. Nando de Freitas
  2. nando de freitas
  3. machine learning
  4. Bayesian learning
  5. predictive distribution
  6. confidence intervals
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Комментарии
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14:30 - 18:14, very good explanation regarding the difference between Bayesian and non-Bayesian approach

heyjianjing
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It looks like the lecture was cut off at the end. Could you upload the rest?

startoftext
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Hi, thanks for the great lectures! Could you please upload the rest of the video?

emmanouiltzouridis
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I think it doesn't make the bar (or uncertainty) lower compared to ML, the term "lower" is compared to the place where we don't have data...

sudao
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at the end, why the extra positive term makes the bar lower when you have data?

ZaikunXu
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