Book Image

C# 9 and .NET 5 – Modern Cross-Platform Development - Fifth Edition

By : Mark J. Price
Book Image

C# 9 and .NET 5 – Modern Cross-Platform Development - Fifth Edition

By: Mark J. Price

Overview of this book

In C# 9 and .NET 5 – Modern Cross-Platform Development, Fifth 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 a new chapter on the Microsoft Blazor framework. The book’s first part teaches the fundamentals of C#, including object-oriented programming and new C# 9 features such as top-level programs, target-typed new object instantiation, and immutable types using the record keyword. Part 2 covers the .NET APIs, for performing tasks like managing and querying data, monitoring and improving performance, and working with the file system, async streams, serialization, and encryption. Part 3 provides examples of cross-platform apps you can build and deploy, such as websites and services using ASP.NET Core or mobile apps using Xamarin.Forms. The best type of application for learning the C# language constructs and many of the .NET libraries is one that does not distract with unnecessary application code. For that reason, the C# and .NET topics covered in Chapters 1 to 13 feature console applications. In Chapters 14 to 20, having mastered the basics of the language and libraries, you will build practical applications using ASP.NET Core, Model-View-Controller (MVC), and Blazor. By the end of the book, you will have acquired the understanding and skills you need to use C# 9 and .NET 5 to create websites, services, and mobile apps.
Table of Contents (23 chapters)
22
Index

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?
  10. What does the score represent with matrix factorization?

Exercise 19.2 – Practice...