Machine Learning Projects Net by Brandewinder Mathias (18 results)

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Taschenbuch. Condition: Neu. Machine Learning Projects for .NET Developers | Mathias Brandewinder | Taschenbuch | xix | Englisch | 2015 | Apress | EAN 9781430267676 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbi…eter: preigu.

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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 300 pp. Englisch.

Language: English
Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG 2015
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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.

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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 pro…ject 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 scratchCode a spam filter that learns by exampleUse 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 predictionsFind patterns in data when you don't know what you're looking forPredict numerical values using regression modelsImplement an intelligent game that learns how to play from experienceAlong 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.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 300 pp. Englisch.

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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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 proj…ect 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 scratchCode a spam filter that learns by exampleUse 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 predictionsFind patterns in data when you don t know what you re looking forPredict numerical values using regression modelsImplement an intelligent game that learns how to play from experienceAlong 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.