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My FREE book about Bayesian Networks, Bayesuvius, continues to grow. It currently has 33 chapters. The purpose of this blog post is to announce the release of a new Bayesuvius chapter on Belief Propagation (BP).
Belief Propagation (BP) (aka Message Passing)was first proposed in 1982 by Judea Pearl to simplify the exact evaluation of probability marginals of…Continue
Decision Trees (DTs) are certainly cool and it is not my intention to belittle them here. Compared to Bayesian Networks (bnets), they seem easier to construct. In fact, I just wrote a poem dedicated to Decision Trees. It starts "I think that I shall never see an AI as lovely as a decision tree". DTs do have some drawbacks, but, like I said, the purpose of this blog post is not to criticize them.
The real purpose of this post is to point out that there is a secret…Continue
It's a question I often wondered about as a child, as I marveled at NYC skyscrapers during my first visit there, or when I visited Cape Canaveral or the Golden Gate Bridge. I don't claim I will provide a full answer to this question in this short post. However, recently, I've been studying two types of tools that are very useful in handling the mindbogglingly numerous details of a complicated project. And I would like to tell you about those 2 tools here. So this is going to…
I recently wrote a popular article on Causal AI. Note that Causal AI is almost exclusively the province of Bayesian networks (bnets), not of their more puny brethren, neural networks (NNs). Indeed, Causal AI is based on Judea Pearl's theory of causality which is expressed via bnets, not NNs.
Something that I didn't mention in my…Continue