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Mastering Visual Studio 2022

You're reading from   Mastering Visual Studio 2022 Develop apps like a pro with advanced Visual Studio techniques using C# and .NET

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Product type Paperback
Published in Dec 2024
Publisher Packt
ISBN-13 9781835884683
Length 324 pages
Edition 1st Edition
Languages
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Author (1):
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Romain Ottonelli  Dabadie Romain Ottonelli Dabadie
Author Profile Icon Romain Ottonelli Dabadie
Romain Ottonelli Dabadie
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Table of Contents (22) Chapters Close

Preface 1. Part 1: Mastering Core Development Skills
2. Chapter 1: Unit Testing and Test-Driven Development FREE CHAPTER 3. Chapter 2: Advanced Debugging Strategies 4. Chapter 3: Advanced Code Analysis and Refactoring 5. Chapter 4: Performance Optimization and Profiling 6. Part 2: Advancing Development Horizons
7. Chapter 5: Multi-Platform App UI Development 8. Chapter 6: Advanced Web Development Tools 9. Chapter 7: Machine Learning Integration 10. Chapter 8: Advanced Cloud Integration and Services 11. Part 3: Streamlining Collaborative Development with DevOps Practices
12. Chapter 9: Handling Advanced Git Workflows 13. Chapter 10: Continuous Integration with GitHub Actions 14. Chapter 11: Collaborative Development with Azure DevOps 15. Chapter 12: Visual Studio Container Tools for Docker 16. Part 4: Mastering Core Development Skills
17. Chapter 13: Writing Your Own Project Template 18. Chapter 14: Writing Your Own Visual Studio Extensions 19. Chapter 15: Creating and Publishing Powerful NuGet Packages for the Community 20. Index 21. Other Books You May Enjoy

Deploying a model in an ASP.NET Core web API

In this section, we will learn how to integrate our ML.NET model into an existing web API. To do so, we will jump to the Consume panel of Model Builder.

Figure 7.9 – Consume

Figure 7.9 – Consume

The Consume panel within Model Builder is a critical tool for integrating our trained ML models into .NET applications. Once we’ve completed the evaluation phase, Model Builder generates a model file and the necessary code to incorporate the model into our application. These models are saved as a .zip file, and the code to load and use our model is added as a new project within our solution. Additionally, Model Builder provides a sample console application that we can run to see our model in action.

The Consume panel gives us options to create projects that consume our model, such as the following:

  • Console app: Generates a .NET console application specifically for making predictions using our model
  • Web API: Sets...
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