Machine Learning for C# Developers
by Fiodar Sazanavets
English | 2025 | ISBN: 9781633435681 | 198 pages | True PDF EPUB | 24.08 MB
by Fiodar Sazanavets
English | 2025 | ISBN: 9781633435681 | 198 pages | True PDF EPUB | 24.08 MB
Create production quality machine learning models in C# without leaving the .NET ecosystem.
Machine Learning for C# Developers teaches you how to build powerful machine learning (ML) models using your C# and .NET skills—no Python required! You’ll learn how to use the innovative ML.NET framework to build a virtual assistant that can recognize objects, classify software errors, estimate salaries from a job description, and more.
In Machine Learning for C# Developers you’ll learn:
Machine learning fundamentals
Supervised, unsupervised, and reinforced model training
Build and train models with C# code
Automating the machine learning process
Machine learning is a powerful tool for forecasting trends, modeling customer behaviors, and identifying other important patterns in your data that will help you make more informed decisions. Recent advances in deep learning make it possible to build powerful ML-driven tools that can do everything from personalized product recommendations to image recognition, to text and code generation. For data scientists and developers, powerful frameworks like ML.NET and automated machine learning (AutoML) systems can greatly enhance your productivity in building, training, and deploying even the most advanced ML models.
about the book
Machine Learning for C# Developers opens up the world of machine learning to C# and .NET developers. In it, you’ll find full coverage of the new ML.NET framework that’s at the forefront of Microsoft’s AI developments. Through careful, step-by-step guidance you’ll learn how to deliver everything from simple machine learning tools to complex deep learning models—no Python required.
This engaging book is a practical guide to building ML models using C#, ML.NET, and AutoML tools. You’ll begin with the basics of machine learning, explained through engaging real-world examples. Next, you’ll discover how ML.NET can streamline common ML tasks, and explore models that grow in complexity from a simple classification algorithm to advanced object detection in images. Throughout the book, you’ll develop an intelligent tool that can give feedback and suggestions on writing clean and well-structured code. Soon, you’ll have mastered universal ML concepts that you can turn to building almost any kind of model.
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