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thirdorderscientist.org | ||
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sriku.org
[AI summary] The article explains how to generate random numbers that follow a specific probability distribution using a uniform random number generator, focusing on methods involving inverse transform sampling and handling both continuous and discrete cases. |
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ryantolsma.com
IVF embryo selection is having a moment. Companies like Orchid Health are pitching parents on the promise of optimizing their future kids for IQ, height, disease resistance, and other desirable phenotypes with celebs and politicians (quietly) leaning in. The tech is real and improving, but the actual upside and long-term vision is limited by some pretty basic math. |
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danieltakeshi.github.io
In my STAT 210A class, we frequently have to deal with the minimum of asequence of independent, identically distributed (IID) random variables. Thishappens b... |
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www.paepper.com
As a data scientist, you are dealing a lot with linear algebra and in particular the multiplication of matrices. Important properties of a matrix are its eigenvalues and corresponding eigenvectors. So let's explore those a bit to get a better intuition of what they tell you about the transformation. We will just need numpy and a plotting library and create a set of points that make up a rectangle (5 points, so they are visually connected in the plot): |
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