Machine Learning with ML.NET

Master ML.NET with C# & .NET 10

Want to build real-world Machine Learning applications using C# and .NET instead of Python?

ML.NET Mastery: Machine Learning with C# & .NET 10 is a practical, production-focused ebook designed for .NET developers who want to move from traditional application development into Machine Learning and AI engineering.

This comprehensive guide takes you from ML fundamentals to production-ready ML applications using C#, .NET 10, ASP.NET Core 10, and ML.NET.

What You’ll Learn

• Machine Learning fundamentals for .NET developers

• Data preparation and feature engineering

• ML.NET architecture and development workflow

• Training, validation, and model evaluation

• Binary and multiclass classification

• Regression and price prediction

• Clustering and customer segmentation

• Anomaly detection and fraud detection

• Recommendation systems

• Time-series forecasting

• Ranking and search relevance

• Natural Language Processing with ML.NET

• Sentiment analysis and email spam detection

• Image classification

• ONNX and pretrained AI models

• AutoML with ML.NET

• ML.NET Model Builder

• ML.NET CLI

• Hyperparameter tuning and model selection

• Feature importance and model explainability

• Model debugging and prediction analysis

• ASP.NET Core model deployment

• Docker and cloud deployment

• ML monitoring, drift detection, and retraining

• Secure and scalable ML architecture

• Production ML platform design

Build Real-World Projects

The ebook goes beyond theory with practical production-style projects, including:

SmartMail — Email Intelligence & Spam Detection
ChurnGuard — Customer Churn Prediction
PriceSense — Product Price Prediction
RecommendX — E-Commerce Recommendation Engine
FraudShield — Fraud Detection Platform

You will learn how to move from:

Data → Features → Training → Evaluation → Model → API → Deployment → Monitoring → Retraining

Designed for .NET Developers

The entire approach is built around the technologies you already know:

C# | .NET 10 | ASP.NET Core 10 | ML.NET | SQL Server | Docker | Cloud

No Python-based ML implementation is required.

The goal is to help you understand how Machine Learning works and how to integrate it into real .NET applications, rather than simply teaching isolated algorithms.

Who Is This Ebook For?

• .NET and C# developers

• Full Stack Developers

• Backend Developers

• Software Engineers

• Technical Leads

• Solution Architects

• Developers transitioning into AI/ML

• Developers building AI-powered applications

• Professionals preparing for ML/AI engineering roles

Whether you're starting your ML journey or already building .NET applications, this ebook provides a structured path from Machine Learning fundamentals to production ML engineering.

Why This Ebook?

This is not just an algorithm reference.

It focuses on the complete engineering lifecycle:

Learn → Build → Train → Evaluate → Deploy → Monitor → Improve

You’ll learn not only what ML.NET APIs do, but also where they fit in a real production architecture and how to use them effectively in .NET applications.

Build intelligent applications with the technology you already know — C# and .NET.

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