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)

Understanding machine learning

Marketing folk love to use terms like artificial intelligence or data science in their promotional materials. Machine learning is a subset of data science. It is one practical way to add intelligence to software.

More Information: You can learn the science behind one of the most popular and successful data science techniques by enrolling in Harvard University's free Data Science: Machine Learning 8-week course at the following link:

This book cannot teach machine learning in one chapter. If you want to know how machine learning algorithms work internally, then you would need to understand data science topics including calculus, statistics, probability theory, and linear algebra. Then you would need to learn about machine learning in depth.

More Information: To learn about machine learning in depth, read Python Machine Learning, Third Edition by Sebastian Raschka...