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Adopting .NET 5

You're reading from   Adopting .NET 5 Understand modern architectures, migration best practices, and the new features in .NET 5

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Product type Paperback
Published in Dec 2020
Publisher Packt
ISBN-13 9781800560567
Length 296 pages
Edition 1st Edition
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Authors (2):
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Hammad Arif Hammad Arif
Author Profile Icon Hammad Arif
Hammad Arif
Habib Qureshi Habib Qureshi
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Habib Qureshi
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Table of Contents (13) Chapters Close

Preface 1. Section 1: Features and Capabilities
2. Chapter 1: Introducing .NET 5 Features and Capabilities FREE CHAPTER 3. Chapter 2: What's New in C# 9? 4. Section 2: Design and Architecture
5. Chapter 3: Design and Architectural Patterns 6. Chapter 4: Containerized Microservices Architecture 7. Section 3: Migration
8. Chapter 5: Upgrading Existing .NET Apps to .NET 5 9. Chapter 6: Upgrading On-Premises Applications to the Cloud with .NET 5 10. Section 4: Bonus
11. Chapter 7: Integrating Machine Learning in .NET 5 12. Other Books You May Enjoy

Building an ML.NET-based service to predict the shopping score

In this section, we will provide a quick introduction to the ML.NET API. After that, we'll perform an exercise in which we'll build a machine learning service that will predict the spending score of a shopping mall customer based on the customer's gender, age, and annual income. The score has been standardized from 1 to 100. The higher the score indicates the higher the spending potential of the customer. Let's see how ML.NET can help us build this service.

Introduction to ML.NET

ML.NET is a free cross-platform .NET Standard library provided by Microsoft so that developers can easily build machine learning-based solutions. It provides APIs for all the usual ML features, such as data acquisition, cleansing, model training, evaluation, and deployment. All major problem types are covered with plenty of well-known machine learning algorithms provided as a built-in feature.

The library is extensible...

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