Mastering .NET Machine Learning - download pdf or read online

By Jamie Dixon

Master the paintings of computing device studying with .NET and achieve perception into real-world applications

About This Book

  • Based on .NET framework 4.6.1, contains examples on ASP.NET middle 1.0
  • Set up what you are promoting program to begin utilizing laptop studying techniques
  • Familiarize the consumer with a number of the extra universal .NET libraries for desktop learning
  • Implement a number of universal laptop studying techniques
  • Evaluate, optimize and regulate computing device studying models

Who This ebook Is For

This publication is concentrated at .Net builders who are looking to construct complicated computer studying platforms. a few easy knowing of knowledge technological know-how is required.

What you'll Learn

  • Write your personal computer studying purposes and experiments utilizing the most recent .NET framework, together with .NET center 1.0
  • Set up your corporation program to begin utilizing desktop learning.
  • Accurately expect the longer term utilizing regressions.
  • Discover hidden styles utilizing determination trees.
  • Acquire, organize, and mix datasets to force insights.
  • Optimize enterprise throughput utilizing Bayes Classifier.
  • Discover (more) hidden styles utilizing KNN and Naive Bayes.
  • Discover (even extra) hidden styles utilizing K-Means and PCA.
  • Use Neural Networks to enhance enterprise determination making whereas utilizing the most recent ASP.NET technologies.
  • Explore “Big Data”, dispensed computing, and the way to set up laptop studying versions to IoT units – making machines self-learning and adapting
  • Along the best way, find out about Open info, Bing maps, and MBrace

In Detail

.Net is without doubt one of the favourite structures for constructing purposes. With the meteoric upward push of computing device studying, builders at the moment are a fan of checking out how can they make their .Net functions smarter. additionally, .NET builders have an interest into entering into the realm of units and the way to use laptop studying suggestions to, good, machines.

This booklet is jam-packed with real-world examples to simply use laptop studying thoughts on your company functions. you'll start with creation to F# and get ready yourselves for computing device studying utilizing .NET framework. you may be writing an easy linear regression version utilizing an instance which predicts revenues of a product. Forming a base with the regression version, you are going to begin utilizing computer studying libraries on hand in .NET framework akin to Math.NET, Numl.NET and Accord.NET with assistance from a pattern program. you'll then circulate directly to writing a number of linear regressions and logistic regressions.

You will examine what's open information and the awesomeness of style companies. subsequent, you will handle the various concerns that we've got been glossing over thus far and take a deep dive into acquiring, cleansing, and organizing our facts. you are going to examine the application of creating a KNN and Naive Bayes version to accomplish very best results.

Implementation of Kmeans and PCA utilizing Accord.NET and Numl.NET libraries is roofed with assistance from an instance program. we are going to then examine a lot of concerns confronting growing real-world laptop studying versions like overfitting and the way to strive against them utilizing confusion matrixes, scaling, normalization, and have choice. you'll now input into the realm of Neural Networks and circulation your line of industrial program to a hybrid medical program. once you have lined all of the above desktop studying types, you will find find out how to care for very huge datasets utilizing MBrace and the way to installation computer studying versions to web of factor (IoT) units in order that the desktop can research and adapt at the fly

Style and process

This booklet will consultant you in studying every thing approximately find out how to take on the flood of information being encountered nowadays on your .NET functions with assistance from renowned computer studying libraries provided through the .NET framework.

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Mastering .NET Machine Learning by Jamie Dixon


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