Jul 2, 2013 — Convolution — I remember in my first image processing course, the instructors threw around the term convolution like flying latkes in this video.  It definitely happens a lot when you are new to a field that people (professors) make assumptions about the jargon of... Read more

Jul 2, 2013 — Elastic Net: Flexible Regularization for Linear Regression — As a reminder, a regularization technique applied to linear regression helps us to select the most relevant features, x, to predict an outcome y.  For now, see my post about LASSO for more details about regularization.  Both LASSO and elastic net,... Read more

Jul 2, 2013 — LASSO: Regularization for Linear Regression — From the mind of the master, we can define lasso as follows: “The Lasso is a shrinkage and selection method for linear regression. It minimizes the usual sum of squared errors, with a bound on the sum of the absolute... Read more

Jul 1, 2013 — Expectation Maximization (EM) Algorithm — Let’s talk about jelly beans.  Specifically, imagine that you took a bag of every single brand of jelly bean in the world (meaning different colors, sizes, and ingredients) and dumped them into a bin.  Your bin now has some k... Read more