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 ...
VentureBeat

You don’t code? Do machine learning straight from Microsoft Excel

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Machine learning and deep learning have ...
Android Police

Machine Learning: Everything you need to know

Ben Khalesi covers the intersection of artificial intelligence and everyday tech at Android Police. With a background in AI and data science, he enjoys making technical topics approachable for those ...
Visual Studio Magazine

Kernel Ridge Regression with Cholesky Inverse Training Using C#

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single ...
ascopubs.org

A Comparison of Logistic Regression Against Machine Learning Algorithms for Gastric Cancer Risk Prediction Within Real-World Clinical Data Streams

TRAIL Score: A Simple Model to Predict Immunochemotherapy Tolerability in Patients With Diffuse Large B-Cell Lymphoma We trained models using logistic regression (LR) and four commonly used ML ...
VentureBeat

What is supervised machine learning?

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More The training process for artificial intelligence (AI) algorithms is ...
ascopubs.org

Development of Machine Learning Algorithms Incorporating Electronic Health Record Data, Patient-Reported Outcomes, or Both to Predict Mortality for Outpatients With Cancer

shinyOPTIK, a User-Friendly R Shiny Application for Visualizing Cancer Risk Factors and Mortality Across the University of Kansas Cancer Center Catchment Area We trained and validated two-phase ML ...