ML.NET Fundamentals: Practice and Learn Machine Learning in C#

Want to build and integrate machine learning models directly into your applications without learning a new programming language? ML.NET makes it possible to leverage your C# skills for AI. This text-only course guides you through the core concepts of ML.NET, helping you understand, write, and validate machine learning pipelines. Through clear explanations and practical self-assessment questions, you will build a solid foundation and test your comprehension every step of the way. What you'll learn: - Understand core machine learning concepts and how they map to the ML.NET API - Build data pipelines for loading, transforming, and preparing data using C# - Train and evaluate regression, classification, and clustering models - Integrate trained models into modern .NET applications using Dependency Injection - Practice self-assessment challenges to validate your understanding of ML.NET workflows - Explore modern patterns like using ONNX models for cross-platform deployment You will start with key terminology and the architecture of the ML.NET framework, then progress to data preparation, model training, and evaluation. Each section includes conceptual explanations followed by written code scenarios and self-test questions to reinforce your learning. This course is designed for .NET developers who are new to machine learning and want a structured, text-based way to learn and test their skills. No prior data science experience is required. Start reading today to master machine learning in your favorite developer ecosystem.