Book Image

C# 8.0 and .NET Core 3.0 – Modern Cross-Platform Development - Fourth Edition

By : Mark J. Price
Book Image

C# 8.0 and .NET Core 3.0 – Modern Cross-Platform Development - Fourth Edition

By: Mark J. Price

Overview of this book

In C# 8.0 and .NET Core 3.0 – Modern Cross-Platform Development, Fourth Edition, expert teacher Mark J. Price gives you everything you need to start programming C# applications. This latest edition uses the popular Visual Studio Code editor to work across all major operating systems. It is fully updated and expanded with new chapters on Content Management Systems (CMS) and machine learning with ML.NET. The book covers all the topics you need. Part 1 teaches the fundamentals of C#, including object-oriented programming, and new C# 8.0 features such as nullable reference types, simplified switch pattern matching, and default interface methods. Part 2 covers the .NET Standard APIs, such as managing and querying data, monitoring and improving performance, working with the filesystem, async streams, serialization, and encryption. Part 3 provides examples of cross-platform applications you can build and deploy, such as web apps using ASP.NET Core or mobile apps using Xamarin.Forms. The book introduces three technologies for building Windows desktop applications including Windows Forms, Windows Presentation Foundation (WPF), and Universal Windows Platform (UWP) apps, as well as web applications, web services, and mobile apps.
Table of Contents (21 chapters)

Practicing and exploring

Test your knowledge and understanding by answering some questions, get some hands-on practice, and explore this chapter's topics with deeper research.

Exercise 19.1 – Test your knowledge

Answer the following questions:

  1. What are the four main steps of the machine learning lifecycle?
  2. What are the three sub-steps of the modeling step?
  3. Why do models need to be retrained after deployment?
  4. Why must you split your dataset into a training dataset and a testing dataset?
  5. What are some of the differences between clustering and classification machine learning tasks?
  6. What class must you instantiate to perform any machine learning task?
  7. What is the difference between a label and a feature?
  8. What does IDataView represent?
  9. What does the count parameter in the [KeyType(count: 10)] attribute represent?
  1. What does the score represent with matrix factorization?

Exercise 19.2 – Practice with samples...