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Learn ML.NET image classification in C#. Step-by-step tutorial to train, evaluate, and deploy a custom image classifier in .NET. Start building today! If you have ever wanted to add image recognition to a .NET app without leaving C#, ML.NET image classification is the fastest way to get there. In this tutorial you will train a custom image classifier in C#, evaluate its accuracy, and deploy the trained model into a production .NET application — all using free, open-source tooling from Microsoft. No Python, no external ML services, and no PhD in deep learning required. ML.NET is Microsoft's cross-platform machine learning framework for .NET developers. It runs on Windows, macOS, and Linux, integrates directly with your existing C# codebase, and uses transfer learning under the hood so you can build an accurate model with only a few hundred images. By the end of this guide you will understand not just how to build an image classifier, but why each step matters. What Is ML....

Learn ML.NET image classification in C#. Train, evaluate, and use a deep learning model to classify images step by step. Start building today! ML.NET image classification lets .NET developers build production-ready computer vision models without leaving C#. If you have ever wanted to train a model that can tell a cat from a dog, detect defective parts on an assembly line, or sort product photos automatically, this tutorial is for you. In this guide you will learn how to perform ML.NET image classification in C# from scratch — loading images, applying transfer learning, training a deep learning model, evaluating accuracy, and using the trained model to make predictions on new images. ML.NET is Microsoft's open-source, cross-platform machine learning framework for .NET. It runs on Windows, Linux, and macOS, integrates directly with ASP.NET Core and console apps, and ships a high-level Image Classification API built on top of TensorFlow. That means you get GPU-accelerated de...