7
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Accepted
What does the notation $\mathcal{N}(z; \mu, \sigma)$ stand for in statistics?
It means that $z$ has a (multivariate) normal distribution with 0 mean and identity covariance matrix. This essentially means each individual element of the vector $z$ has a standard normal ...
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4
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Are Bayesian networks important to learn in 2018?
*AI, A Modern Approach," was given that title to break from previously narrow approaches to duplicating desirable qualities of human thinking.
Although Bayesian networks require somewhat resource ...
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Accepted
Is there an entry level textbook on Bayesian Inference that is a nice blend of theory and applications?
Using as a best reference accordingly my own google research, find the best post about best introductory Bayesian statistics book and summarize the answers. I find this post in stats.stackexchange ...
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Why do Bayesian algorithms work well with small datasets?
The main reason should be that Bayesian algorithms naturally incorporate a form of regularisation (the prior), so they should be less prone to over-fitting the small dataset. Of course, the choice of ...
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Are Bayesian networks important to learn in 2018?
The chapters for Bayesian Networks are:
Quantifying Uncertainty
Probabilistic Reasoning
Dynamic Bayesian
don't forget:
Naive Bayes, hidden variables, Markov
Maybe helpful:
. Are We Going in the ...
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