Scalable sentiment analysis
A collection of samples demonstrating how to use ML.NET for various machine learning tasks in .NET applications.
What is Scalable sentiment analysis?
ML.NET Samples is a GitHub repository containing example code and applications that demonstrate how to use ML.NET, Microsoft's open-source machine learning framework for .NET. It provides practical implementations for various machine learning tasks, helping .NET developers learn how to build, train, and deploy ML models within their applications. The samples range from simple console apps for specific ML tasks to complete end-to-end web and desktop applications.
.NET developers who want to incorporate machine learning into their applications, particularly those new to ML.NET or looking for reference implementations for specific ML tasks like classification, regression, or recommendation systems.
Developers choose ML.NET Samples because it provides production-ready, well-documented examples directly from the ML.NET team, covering a wide range of ML tasks and integration scenarios. It serves as the official learning resource for ML.NET, offering both beginner-friendly getting-started samples and advanced end-to-end application patterns.
Overview
Samples for ML.NET, an open source and cross-platform machine learning framework for .NET.
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