Understand what is Linear Regression Gradient Descent in Machine Learning and how it is used. Linear Regression Gradient ...

This project implements full-batch gradient descent (FBGD) for linear regression, comparing CPU serial and GPU implementations. The assignment demonstrates: assignment-5-linear-regression/ ├── ...

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses stochastic gradient descent, one of two ...

The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict a person's bank savings account balance based on their age, years of ...

Struggling to understand how logistic regression works with gradient descent? This video breaks down the full mathematical derivation step-by-step, so you can truly grasp this core machine learning ...

Abstract: Weight learning forms a basis for the machine learning and numerous algorithms have been adopted up to date. Most of the algorithms were either developed in the stochastic framework or aimed ...

This project explores linear regression using both the least squares method and gradient descent. It implements the matrix form of linear regression and applies it to a real-world dataset. The ...

ABSTRACT: Monitoring of PM10 and PM2.5 concentrations frequently is essential for assessing air quality and informing pollution control strategies. This study examines the effect of height on PM2.5 ...