Object detection using local environments is now available in ML.NET Model Builder to help you solve computer vision problems using machine learning.
Learn what ChatGPT is and how you can get started using GPT models in conversations with Azure OpenAI service and .NET
Learn what prompt engineering is and how to use it to improve the quality of your GPT completions.
This post will show you how to train a custom image classification model in Azure to categorize flowers using ML.NET Model Builder. Then, you can leverage your existing .NET skills to consume the trained model inside a C# .NET Core console application. Best of all, little to no prior machine learning knowledge is required.
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!
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. https://github.com/dotnet/machinelearning Star Get Started @ http://dot.net/ml ML.NET allows you to train, build and ship c...
Overview Tensor is an exchange type for homogenous multi-dimensional data for 1 to N dimensions. The motivation behind introducing Tensor<T> is to make it easy for Machine Learning library vendors like CNTK, Tensorflow, Caffe, Scikit-Learn to port their libraries over to .NET with minimal dependencies in place. Tensor<T> is designed t...
