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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

Exploring additional production application enhancements

Now that we have completed our deep dive, there are a couple of additional elements to further enhance the application. A few ideas are discussed in the upcoming sections.

Logging

As noted previously, the importance of logging cannot be stressed enough within desktop applications. Logging utilizing NLog (https://nlog-project.org/) or a similar open-source project is highly recommended as your application complexity increases. This will allow you to log to a file, console, or third-party logging solution such as Loggly, at varying levels. For instance, if you deploy this application to a customer, breaking down the error level to at least Debug, Warning, and Error will be helpful when debugging issues remotely.

Image scaling

As you might have noticed, with images that are quite large (those exceeding your screen resolution), the text labeling of the bounding boxes and resizing within the image preview is not as easy to read as for...

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