# matrix

## How to Rank Entities with Multi-Criteria Decision Making Methods(MCDM)

Introduction Ranking with MCDM You can’t rest on your #1 ranking-because the guy at #2 isn’t resting. He’s still improving…

## Convex function of diagonals and eigenvalues

Sam Walters posted an elegant theorem on his Twitter account this morning. The theorem follows the pattern of an equality…

## Everything you Should Know about Confusion Matrix for Machine Learning

Confusion Matrix – Not So Confusing! Have you been in a situation where you expected your machine learning model to…

## An application of Kronecker products

A while back I wrote about Kronecker products in the context of higher order Taylor series. Here’s how I described…

## Understanding Class Sensitivity in Classification Problems (using a CIFAR-10 Case Study!)

Overview A fascinating deep dive into the problem of how many classes should you use in a classification problem The…

## Illustrating Cayley-Hamilton with Python

If you take a square matrix M, subtract x from the elements on the diagonal, and take the determinant, you…

## Master Dimensionality Reduction with these 5 Must-Know Applications of Singular Value Decomposition (SVD) in Data Science

3 Ways to Perform SVD in Python   Applications of Singular Value Decomposition (SVD) We are going to follow a…

## Attention in Neural Networks

Let’s look at another example, “Post photos in your Dropbox folder to Instagram”. Compared to the previous one, here “Instagram”…

## Linear Algebra. Points matching with SVD in 3D space

Linear Algebra. Points matching with SVD in 3D spaceAndrey NikishaevBlockedUnblockFollowFollowingJun 30ProblemWe need to find best rotation & translation params between two…

## Recommendation Systems using UV-Decomposition

Maybe if we had additional features other than just movie series there might be some other similarities between the Star…

## An introduction to SVD and its widely used applications

An introduction to SVD and its widely used applicationsNathan ToubianaBlockedUnblockFollowFollowingJun 1If you’re in the data science world (or close to…

## Annotated Heatmaps in 5 Simple Steps

Annotated Heatmaps in 5 Simple StepsJulia KhoBlockedUnblockFollowFollowingMay 31A heatmap is a graphical representation of data in which data values are represented…

## Introduction to Latent Matrix Factorization Recommender Systems

Introduction to Latent Matrix Factorization Recommender SystemsTumas RackaitisBlockedUnblockFollowFollowingMay 30Latent Factors are “Hidden Factors” unseen in the data set. Lets use…

## Multi-Dimension Scaling

Dimension ReductionMulti-Dimension Scalingin PythonDiogo RibeiroBlockedUnblockFollowFollowingMay 29Photo by Lukasz Szmigiel on UnsplashMulti-Dimension Scaling is a distance-preserving manifold learning method. All manifold learning…

## Linear Classifiers: An Overview

Linear Classifiers: An OverviewThis article discusses the mathematical properties and practical Python applications of four popular linear classification methods. Michał OleszakBlockedUnblockFollowFollowingMay…

## Matrix in Python-Part1

Matrix in Python-Part1trainer. cppBlockedUnblockFollowFollowingMay 17In this story and next few parts we will see what is matrix both mathematically and…

## Practical Introduction to Hartree-Fock

Practical Introduction to Hartree-FockLaksh AithaniBlockedUnblockFollowFollowingMay 7We will write a Hartree-Fock algorithm completely from scratch in Python and use it to…

## An overview of Principal Component Analysis

How will it look?Variance is the expectation of the squared deviation of a random variable from its mean. Informally, it…

## Singular Value Decomposition vs. Matrix Factoring in Recommender Systems

I had to dig a little bit, but eventually, I found some hidden gems. According to Luis Argerich:The matrix factorization…

## Principal Component Analysis — Math and Intuition (Post 3)

I hope you chose the black line as it is closer to most of the data points (see figure below).…

## Principal Component Analysis — Math and Intuition (Post 2)

Principal Component Analysis — Math and Intuition (Post 2)Shivangi PatelBlockedUnblockFollowFollowingApr 4This is Post 2 of a 3-part series on Principal Component Analysis — Math and…

## Introduction to Convolutional Neural Networks (CNN) with TensorFlow

Introduction to Convolutional Neural Networks (CNN) with TensorFlowLearn the foundations of convolutional neural networks for computer vision and build a…

## Building a Music Recommendation Engine with Probabilistic Matrix Factorization in PyTorch

However, it should be noted that each of these matrices are randomly initialized. Therefore, in order for these predictions and…

## Random forest text classification in R: Trump v. Obama

Random forest text classification in R: Trump v.  ObamaCan I successfully determine the differences in speech content between the 2…

## PCA and SVD explained with numpy

PCA and SVD explained with numpyZichen WangBlockedUnblockFollowFollowingMar 16How exactly are principal component analysis and singular value decomposition related and how to…