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Hands-On Machine Learning with ML.NET

You're reading from   Hands-On Machine Learning with ML.NET Getting started with Microsoft ML.NET to implement popular machine learning algorithms in C#

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Product type Paperback
Published in Mar 2020
Publisher Packt
ISBN-13 9781789801781
Length 296 pages
Edition 1st Edition
Languages
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Author (1):
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Jarred Capellman Jarred Capellman
Author Profile Icon Jarred Capellman
Jarred Capellman
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Toc

Table of Contents (19) Chapters Close

Preface 1. Section 1: Fundamentals of Machine Learning and ML.NET
2. Getting Started with Machine Learning and ML.NET FREE CHAPTER 3. Setting Up the ML.NET Environment 4. Section 2: ML.NET Models
5. Regression Model 6. Classification Model 7. Clustering Model 8. Anomaly Detection Model 9. Matrix Factorization Model 10. Section 3: Real-World Integrations with ML.NET
11. Using ML.NET with .NET Core and Forecasting 12. Using ML.NET with ASP.NET Core 13. Using ML.NET with UWP 14. Section 4: Extending ML.NET
15. Training and Building Production Models 16. Using TensorFlow with ML.NET 17. Using ONNX with ML.NET 18. Other Books You May Enjoy
Section 2: ML.NET Models

This section talks about using the various trainers available in ML.NET as of version 1.1. In each chapter, a detailed deep dive into the trainer, math, and how to use it with ML.NET will be conveyed.

This section comprises the following chapters:

  • Chapter 3, Regression Model
  • Chapter 4, Classification Model
  • Chapter 5, Clustering Model
  • Chapter 6, Anomaly Detection Model
  • Chapter 7, Matrix Factorization Model
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