DreamozTech

  Download Your Copy Here   Integrating AI/ML-driven features like prediction services and classification engines into a .NET Core Web API is a powerful way to add intelligence to your applications. Here's a breakdown of good tools, resources, and approaches to consider: Key Approaches to AI/ML Integration with .NET Core There are generally two main ways to integrate AI/ML into your .NET Core Web API: Using ML.NET: This is Microsoft's open-source, cross-platform machine learning framework built specifically for .NET developers. It allows you to build, train, and deploy custom ML models directly within your .NET applications using C# or F#.   Consuming External AI/ML Services/APIs: This involves leveraging pre-built or custom-trained models hosted as services (e.g., in the cloud like Azure Machine Learning, Google Cloud AI, AWS ML services, or third-party AI APIs like OpenAI). Your .NET Core Web API then acts as a client ...