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EM Topic Modeling – Hands-On, Easy, and Detailed Expectation Maximization for Topic Modeling Using the fabricated data, this document outlines the implementation of the Expectation Maximization (EM) algorithm for topic modeling. The EM algorithm is a two-step process involving an Expectation step (E-Step) followed by a Maximization step (M-Step). All logarithms in this post are…

PCoA Tutorial Part 1: Distance Matrix In this guide, we’ll walk through Principal Coordinates Analysis (PCoA) with data that’s meant to simulate the CIFAR-10 dataset. For more information on CIFAR-10, you can read up on it here: https://www.cs.toronto.edu/~kriz/cifar.html. We’ll start with understanding our data, then dive into creating a distance matrix to see how different…

Mean Squared Error (MSE) is a widely used metric for measuring the accuracy of a model in regression analysis, representing the average squared difference between the estimated values and the actual value. In the context of linear algebra, Singular Value Decomposition (SVD) offers a powerful method for solving linear systems, including those involved in calculating…