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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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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

Summary

In this chapter, you have learned the importance of discovering machine learning. In addition, you have also learned the core concepts of machine learning, including the differences in learning and the various algorithms we will cover later in this book. You have also received an introduction to ML.NET. The core concepts in this chapter are the foundation for the rest of the book and we will be building on them with each subsequent chapter. In the next chapter, we will be setting up your environment and training your first model in ML.NET!

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Hands-On Machine Learning with ML.NET
Published in: Mar 2020
Publisher: Packt
ISBN-13: 9781789801781
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