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The expert guide to creating production machine learning solutions with ML.NET!
ML.NET brings the power of machine learning to all .NET developers and Programming ML.NET helps you apply it in real production solutions. Modeled on Dino Espositos best-selling Programming ASP.NET, this book takes the same scenario-based approach Microsofts team used to build ML.NET itself. After a foundational overview of ML.NETs libraries, the authors illuminate mini-frameworks (ML Tasks) for regression, classification, ranking, anomaly detection, and more. For each ML Task, they offer insights for overcoming common real-world challenges. Finally, going far beyond shallow learning, the authors thoroughly introduce ML.NET neural networking. They present a complete example application demonstrating advanced Microsoft Azure cognitive services and a handmade custom Keras network showing how to leverage popular Python tools within .NET.
14-time Microsoft MVP Dino Esposito and son Francesco Esposito show how to:
Follow the instructions to download this book's lesson files.
Download the sample pages (includes Chapter 2)
CHAPTER 1 Artificially Intelligent Software
CHAPTER 2 An Architectural Perspective of ML.NET
CHAPTER 3 The Foundation of ML.NET
CHAPTER 4 Prediction Tasks
CHAPTER 5 Classification Tasks
CHAPTER 6 Clustering Tasks
CHAPTER 7 Anomaly Detection Tasks
CHAPTER 8 Forecasting Tasks
CHAPTER 9 Recommendation Tasks
CHAPTER 10 Image Classification Tasks
CHAPTER 11 Overview of Neural Networks
CHAPTER 12 A Neural Network to Recognize Passports
APPENDIX A Model Explainability