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2015-07-29

Machine Learning Projects for .NET Developers


Book Description
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.

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.
Book Details
Publisher:        Apress
By:        Mathias Brandewinder
ISBN:        978-1-4302-6767-6
Year:        2015
Pages:        300
Language:        English
File size:        7.5 MB
File format:        PDF
eBook
Download:        Machine Learning Projects for .NET Developers

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2015-8-2 23:07:02

Listing 2-1. Reading the SMS dataset from the file

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2015-8-2 23:11:48

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2015-8-2 23:13:34

Listing 2-2. Scoring a document

Assuming a document has already been broken into a set of tokens, computing its score for a given group is fairly simple. We don’t have to worry about how these numbers have been computed. If that part has been done already, all we need to do is sum up the log of the group frequency, as well as the log of every token that is present in both the tokenized document and the list of tokens we are using in our model:
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2015-8-2 23:18:26

Listing 2-3. Predicting the label of a document

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2015-8-2 23:20:25

Listing 2-4. Analyzing a group of documents

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