https://github.com/rijwanansari/dotnet9sampleaiapps
.NET 9 helps with AI-driven development, focusing on how to use machine learning models, and walk through a sample project
https://github.com/rijwanansari/dotnet9sampleaiapps
aiapps anomaly-detection dotnet dotnet-core mlnet sentiment-analysis
Last synced: about 2 months ago
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.NET 9 helps with AI-driven development, focusing on how to use machine learning models, and walk through a sample project
- Host: GitHub
- URL: https://github.com/rijwanansari/dotnet9sampleaiapps
- Owner: rijwanansari
- Created: 2025-02-25T11:44:24.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2025-04-03T04:06:45.000Z (about 2 months ago)
- Last Synced: 2025-04-03T04:29:10.337Z (about 2 months ago)
- Topics: aiapps, anomaly-detection, dotnet, dotnet-core, mlnet, sentiment-analysis
- Language: C#
- Homepage:
- Size: 5.49 MB
- Stars: 3
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
## AI Meets .NET: Building Intelligent Apps with .NET 9
The combination of artificial intelligence (AI) and modern software development is changing the way we build applications. With the release of .NET 9, Microsoft keeps giving developers tools and frameworks that make it easy to add AI capabilities to strong, scalable applications.
In this article, we’ll look at how .NET 9 helps with AI-driven development, focusing on how to use machine learning models, and walk through a sample project—an intelligent sentiment analysis API—complete with example code.
### Why .NET 9 for AI Development?
.NET 9 has some great new features, like better performance, better support for cloud-native apps, and a refined ecosystem that works really well with AI workloads. It’s got APIs that are super simple, better AOT (Ahead-of-Time) compilation, and better integration with containers, so it’s a great choice for building intelligent, high-performance apps. On top of that, libraries like ML.NET and compatibility with popular AI frameworks like TensorFlow and ONNX let developers embed AI right into their .NET solutions.
### Setting the Stage: Tools and Prerequisites
To follow along, you’ll need:
Visual Studio or VS code with .NET 9 SDK: Install the latest version from the official Microsoft site. For coding and debugging. I will be using VS code for the demo project.
- ML.NET: A machine learning framework for .NET (install via NuGet: Microsoft.ML).
- A Basic Understanding of ASP.NET Core: For building the API.
### Project Overview: Sentiment Analysis API
Let’s build a simple ASP.NET Core Web API that uses ML.NET to do sentiment analysis on text submitted by users. The API will predict if a text expresses positive or negative sentiment, which is a great starting point for AI-driven apps.
### Complete Article
https://dotnetcopilot.com/ai-meets-net-building-intelligent-apps-with-net-9/