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 first chapter of Neural Networks, Tricks of the Trade strongly advocates the stochastic back-propagation method to train neural networks. This is in fact an instance of a more general technique ...

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 ...

Language-based agentic systems represent a breakthrough in artificial intelligence, allowing for the automation of tasks such as question-answering, programming, and advanced problem-solving. These ...

This study provides a computable, direct, and mathematically rigorous approximation to the differential geometry of class manifolds for high-dimensional data, along with non-linear projections from ...

Abstract: Hierarchical-multivariate spectral gradient method is proposed for unconstrained optimization problems. It is a compound of multivariate spectral gradient method and two-point stepsize ...

Cameron Lucas is a writer who has been dedicated to the medium for over four years, and an avid player of video games for all of his life. After the better part of a year at Game Rant as a feature ...

This article illustrates how to build, in less than 5 minutes, a simple linear regression model with gradient descent. The goal is to predict a dependent variable (y) from an independent variable (X).