InfoWorld

Machine learning: Demystifying linear regression and feature selection

Businesspeople need to demand more from machine learning so they can connect data scientists’ work to relevant action. This requires basic machine learning literacy — what kinds of problems can ...
ascopubs.org

Comparative Evaluation of Explainable Machine Learning Versus Linear Regression for Predicting County-Level Lung Cancer Mortality Rate in the United States

This study applied three models—random forest (RF), gradient boosting regression (GBR), and linear regression (LR)—to predict county-level LC mortality rates across the United States. Model ...
Analytics Insight

Machine Learning, Stanford University

Stanford University’s Machine Learning (XCS229) is a 100% online, instructor-led course offered by the Stanford School of ...
CU Boulder News & Events

DTSA 5509 Introduction to Machine Learning: Supervised Learning

Use modern machine learning tools and python libraries. Explain how to deal with linearly-inseparable data. Compare logistic regression’s strengths and weaknesses. Explain what decision tree is & how ...
Analytics Insight

10 Must-Know Machine Learning Algorithms for Data Science in 2026

Machine learning algorithms help computers analyse large datasets and make accurate predictions automatically.Classic models ...
Visual Studio Magazine

Kernel Ridge Regression with Stochastic Gradient Descent Training Using JavaScript

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 ...
Visual Studio Magazine

Kernel Ridge Regression with Stochastic Gradient Descent Training Using C#

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 ...