DateFeb 18, 2019
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What is “learning” and do we have a formal model for it? I’ve decided to dive into the theoretical underpinnings of machine-learning, so here’s a quick introduction to...
In this article, we define underfitting and overfitting and show some nice ways to vizualize them on polynomial regressions.
In this article we will derive the normal distribution as the probability distribution that models measurement errors. We start with a dart game and follow Herschel’s derivation.
In a previous article I showed that the inference rules of propositional logic can be obtained from probability calculus. But actually, we can obtain much more, and even...
In this article, I will apply the rules of probability calculus to derive the rules of propositional logic (also called propositional calculus).
The aim of this article is to illustrate what are probability theory and statistical inference in simple terms using a simple to understand problem: drawing colored balls from an urn.
This article sketches a construction of probability calculus as an extension of classical logic to account for uncertainty so that by construction, it can be used to automate...