Machine learning projects for .NET Developers [electronic resource] / Mathias Brandewinder.

Unlimited

Authorized users

Can lend chapters, not whole ebooks

Machine learning projects for .NET Developers [electronic resource] / Mathias Brandewinder.

9781430267669 electronic book
1430267666 electronic book
9781430267676

Berkeley, CA : Apress, 2015.

New York, NY : Distributed to the book trade worldwide by Springer,

©2015

English

1 online resource (xix, 275 pages) : illustrations

Q325.5 .B73 2015eb

006.3/1

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: Build an optical character recognition (OCR) system from scratch Code a spam filter that learns by example Use F♯'s powerful type providers to interface with external resources (in this case, data analysis tools from the R programming language) Transform your data into informative features, and use them to make accurate predictions Find patterns in data when you don't know what you're looking for Predict numerical values using regression models Implement an intelligent game that learns how to play from experience 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.

Includes index.

Access limited to authorized users.

Online resource; title from PDF title page (SpringerLink, viewed July 13, 2015).

Online Resources > Ebooks
All Resources