Take the ML.NET survey to let us know what you want to see next for Machine Learning in .NET.
This release of ML.NET and Model Builder brings numerous bug fixes and enhancements as well as new features, including config-based training and a redesigned Consume step.
A GitHub Action harnessing Azure Cognitive Services Translator to automatically create translation files.
This release of ML.NET Model Builder brings numerous bug fixes and enhancements as well as new features, including advanced data loading options and streaming training data from SQL.
Machine Learning Operations (MLOps) is like DevOps for the machine learning lifecycle. This includes things like model deployment & management and data tracking, which help with productionizing machine learning models. Through the survey below, we'd love to get feedback on your current DevOps practices as well as your prospective usage of ML...
This release of ML.NET (1.5.2) brings numerous bug fixes and enhancements, while tooling updates include the ability to train object detection models using Azure ML via Model Builder and to locally train image classification models with the ML.NET CLI.
The specification defines many floating point types, including: , , and . Most developers are familiar with (equivalent to in C#) and (equivalent to in C#). They provide a standard format to represent a wide range of values with a precision acceptable for many applications. .NET has always had and and with .NET 5 Preview 7, we've added a ne...
ML.NET is an open-source, cross-platform machine learning framework for .NET developers. It enables integrating machine learning into your .NET apps without requiring you to leave the .NET ecosystem or even have a background in ML or data science. ML.NET provides tooling (Model Builder UI in Visual Studio and the cross platform ML.NET CLI) that aut...
With the ML.NET Model Builder, create custom machine learning models for scenarios like sentiment analysis, price prediction, and more without any machine learning experience and without leaving the .NET ecosystem!
Last month, we announced .NET support for Jupyter notebooks, and showed how to use them to work with .NET for Apache Spark and ML.NET. Today, we're announcing the preview of a DataFrame type for .NET to make data exploration easy. If you've used Python to manipulate data in notebooks, you'll already be familiar with the concept of a DataFrame. At a...
