This requires basic machine learning literacy — what kinds of problems can machine learning solve, and how to talk about those problems with data scientists. Linear regression and feature ...

Regression analysis is nothing new to data science, but when you apply machine learning, AI can simplify the process. However, the data you give the machine will really make a difference in the ...

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 ...

Recently, artificial intelligence (AI) using machine learning (ML) technology has become available to automatically analyze, bin, triage, probe, and discover the root causes of regression failures. By ...

Machine learning (ML) technologies have enabled an automated debug process that not only accelerates debug but also eliminates errors introduced by manual efforts. This white paper discusses how ...

Linear Regression Cost function in Machine Learning is "error" representation between actual value and model predictions. To minimize the error, we need to minimize the Linear Regression Cost ...

Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.