— Generalized Linear Models (GLM) — If you think of regression (e.g., linear with gaussian distributions) and classification (logisitic with bernoulli) as cousins, they belong under the larger family of General Linear Models. A GLM is a broad family of models that can all be simplified to a... Read more
Hi, I'm VanessaSaurus, a Software Engineer.
Building tools, containers, and cloudy things, with a penchant for Python and parsnips. -- about me
Raaawwr..!
— Laplace Smoothing — Why do we need Laplace Smoothing? Let’s return to the problem of using Naive Bayes to classify a recipe as “ice cream”(1) or “sorbet” (2) based on the ingredients (x). When we are calculating our posterior probabilities, or the probability... Read more
— Naive Bayes — Naive Bayes is a supervised, probabilistic classification method for discrete classes that makes some strong assumptions about the data, but works pretty well. If you think back to regression, regression, we were trying to predict p(y x), and this is... Read more
— Diffusion Tensor Imaging (DTI) — Diffusion Tensor Imaging looks at white matter integrity. It is a MRI based method that uses diffusion properties of water molecules to construct white matter fibers (anatomical connections) between brain regions. There are many metrics of white matter tracts you... Read more