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Monday, March 2, 2015

The amazing CountBasie blog posts Bayes Explained with Lego.

If you want an easy explanation of Bayes Theorem, I can tell you where to find it. Bayes theorem is a counter-intuitive brain-twister in elementary probability theory (wikipedia formula below)

P(H\mid E) = \frac{P(E\mid H)}{P(E)} \cdot P(H)

which allows one to infer the conditional probability "The expectation Annie likes Chocolate if I already know she likes Strawberries" from the conditional probability of "The expectation Annie likes Strawberries if I already know she likes Chocolate". This allows you to go from what you've observed to what you'd like to know about, so I guess it's in hidden but everyday use in much of science and real life calculations. 

A lot of AI algorithms eg. evolutionary computation are stochastic, but I didn't know there is a blog devoted to explaining probability theory. I guess there all kinds of perverts out there on the net these days (JOKE). Anyway the site is called Count Bayesie — possibly a pun on the cyberpunk Count Zero. Posts have complicated titles and really amazing graphics like this one. 

However this blog's 15 minutes of Internet fame doubtless came with the superb post entitled Bayes theorem explained with Lego. Now that I've warmed you up, you can go directly to CountBasie's lego demo. I've linked to the image below because it is so cute it went viral. 

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