Learning F# Functional Data Structures and Algorithms
Machine Learning Projects for .NET Developers shows you how to build smarter .NET applications that learn from data, using simple algorithms and techniques that can be applied to a wide range of real-world problems. You’ll code each project in the familiar setting of Visual Studio, while the machine learning logic uses F#, a language ideally suited to machine learning applications in .NET. If you’re new to F#, this book will give you everything you need to get started. If you’re already familiar with F#, this is your chance to put the language into action in an exciting new context.
In a series of fascinating projects, you’ll learn how to:
Along the way, you’ll learn fundamental ideas that can be applied in all kinds of real-world contexts and industries, from advertising to finance, medicine, and scientific research. While some machine learning algorithms use fairly advanced mathematics, this book focuses on simple but effective approaches. If you enjoy hacking code and data, this book is for you.
Machine Learning Projects for .NET Developers is for intermediate to advanced .NET developers who are comfortable with C#. No prior experience of machine learning techniques is required. If you’re new to F#, you’ll find everything you need to get started. If you’re already familiar with F#, you’ll find a wealth of new techniques here to interest and inspire you.
While some machine learning algorithms use fairly advanced mathematics, this book focuses on simple but effective approaches and how they can be used in actual code. If you enjoy hacking code and data, this book is for you.
Country | USA |
Author | Mathias Brandewinder |
Binding | Kindle Edition |
Edition | 1 |
EISBN | 9781430267669 |
Format | Kindle eBook |
Label | Apress |
Manufacturer | Apress |
NumberOfPages | 302 |
PublicationDate | 2015-06-29 |
Publisher | Apress |
ReleaseDate | 2015-06-29 |
Studio | Apress |