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Questions and Comments

[Review by Hariharan Seshadri]:

• This is a very well developed slecture on Bayesian Parametric Estimation (BPE)

[Review by Hariharan Seshadri]:

• What I like about this slecture is that the author is organized in his/her thoughts.

[Review by Hariharan Seshadri]:

• The author starts of by giving a general introduction to Bayesian Parametric Distribution, and goes on to derive the parameters (mean and std. deviation) of the distribution of the MEAN of a univariate Gaussian Distribution (Assuming that the MEAN is a Normally Distributed Random Variable and also assuming that the some prior information about the MEAN is already known along with the parameters of the distribution from which the samples were obtained from)

[Review by Hariharan Seshadri]:

• Having obtained these parameters of the MEAN, the author goes on to derive the conditional probability of p(x|D) using the afore-mentioned parameters

[Review by Hariharan Seshadri]:

• The author is methodical in the derivation

[Review by Hariharan Seshadri]:

• To make this great slecture even better, the author could compare the accuracy of BPE and MLE in a classification context (just like HW 2 - Spring 2014). In short, it was a very informative slecture

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