Microsoft Research's Dr. James McCaffrey show how to perform binary classification with logistic regression using the Microsoft ML.NET code library. The goal of binary classification is to predict a ...

Dr. James McCaffrey provides hands-on examples in introducing ML.NET, for machine learning prediction models, and AutoML, which automatically examines different ML algorithms, finds the best one, and ...

Getting started with ML.Net is easy. First download and install the ML.Net packages, and then add the appropriate libraries to your .Net code, declaring them in your headers with using statements.

Learn how to use data governance for AI and ML systems effectively with this comprehensive guide, covering insights and best practices.

.NET developers, across platforms, now have access to machine learning from their home turf. Microsoft Automated Machine Leaning (AutoML) is included, and a Model Builder extension for Visual ...

And ML.NET 3.0 gains new automated machine learning (AutoML) capabilities including the AutoML Sweeper now supporting sentence similarity, question answering, and object detection.