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7 votes

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 ...
David's user avatar
  • 4,920
4 votes

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 ...
Douglas Daseeco's user avatar
1 vote

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 ...
rubengavidia0x's user avatar
1 vote

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 ...
nbro's user avatar
  • 40.8k
1 vote

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 ...
PrivateStatic's user avatar

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