Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Adopting .NET 5

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

Arrow left icon
Product type Paperback
Published in Dec 2020
Publisher Packt
ISBN-13 9781800560567
Length 296 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Authors (2):
Arrow left icon
Hammad Arif Hammad Arif
Author Profile Icon Hammad Arif
Hammad Arif
Habib Qureshi Habib Qureshi
Author Profile Icon Habib Qureshi
Habib Qureshi
Arrow right icon
View More author details
Toc

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...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image