Machine Learning Projects for .NET Developers

Mathias Brandewinder

ISBN 10: 1430267674 / ISBN 13: 9781430267676

Verlag: Apress 08 D, 2015

Beschreibung

Machine Learning Projects for .NET Developers This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. .

Bestandsnummer des Verkäufers 7719-9781430267676

Bibliografische Details

• Titel: Machine Learning Projects for .NET Developers
• Verlag: Apress 08 D
• Erscheinungsjahr: 2015
• Sprache: Englisch
• ISBN-10: 1430267674
• ISBN-13: 9781430267676
• Einband: Paperback
• Zustand: Very Good

Über diesen Titel

Inhaltsangabe

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 intoinformative 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.

Über die Autorin bzw. den Autor

Mathias Brandewinder is a Microsoft MVP for F# based in San Francisco, California. An unashamed math geek, he became interested early on in building models to help others make better decisions using data. He collected graduate degrees in Business, Economics and Operations Research, and fell in love with programming shortly after arriving in the Silicon Valley. He has been developing software professionally since the early days of .NET, developing business applications for a variety of industries, with a focus on predictive models and risk analysis.