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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 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.
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