How to use ML.NET CLI Getting Started with ML.NET using Model Builder

In this particular case, in only 10 seconds and with the small dataset provided, the CLI tool was able to run quite a few iterations, meaning training multiple times based on different combinations of algorithms/configuration with different internal data transformations and algorithm's hyper-parameters. Finally, the "best quality" model found in 10 seconds is a model using a particular trainer/algorithm with any specific configuration. Depending on the exploration time, the command can produce a different result. The selection is based on the multiple metrics shown, such as Accuracy. The first and easiest metric to evaluate a binary-classification model is the accuracy, which is simple to understand. "Accuracy is the proportion of correct predictions with a test data set.".

We are excited to announce ML.NET 1.2 and updates to Model Builder and the CLI. ML.NET is an open-source and cross-platform machine learning framework for .NET developers. ML.NET also includes Model Builder (a simple UI tool for Visual Studio) and the ML.NET CLI (Command-line interface) to make it super easy to build custom Machine Learning (ML) models using Automated Machine Learning (AutoML). Using ML.NET, developers can leverage their existing tools and skill-sets to develop and infuse custom ML into their applications by creating custom machine learning models for common scenarios like Sentiment Analysis, Price Prediction, Image Classification and more! ML.NET 1.2 is a backwards compatible release with no breaking changes so please update to get the latest changes.

We are excited to announce the release of ML.NET 1.0 today. ML.NET is a free, cross-platform and open source machine learning framework designed to bring the power of machine learning (ML) into .NET applications. ML.NET allows you to train, build and ship custom machine learning models using C# or F# for scenarios such as sentiment analysis, issue classification, forecasting, recommendations and more. You can check out these common scenarios and tasks at our ML.NET samples repo. ML.NET was originally developed within Microsoft Research, and evolved into a significant framework used by many Microsoft products such as Windows Defender, Microsoft Office (Powerpoint design ideas, Excel Chart recommendations), Azure Machine Learning, PowerBI key influencers to name a few!