Machine Learning Projects for .NET Developers
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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...
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 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 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.
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 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.
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