Machine Learning Using C# Succinctly by James McCaffrey
English | True PDF | 2014 | 148 Pages | ISBN : N/A | 2.12 MB
In Machine Learning Using C# Succinctly, you’ll learn several different approaches to applying machine learning to data analysis and prediction problems. Author James McCaffrey demonstrates different clustering and classification techniques, and explains the many decisions that must be made during development that determine how effective these techniques can be. McCaffrey provides thorough examples of applying k-means clustering to group strictly numerical data, calculating category utility to cluster both qualitative and quantitative information, and even using neural network classification to predict the output of previously unseen data.
TABLE OF CONTENTS

k-Means Clustering

Categorical Data Clustering

Logistic Regression Classification

Naïve Bayes Classification

Neural Network ClassificationVisit My Blog For Daily Very Exclusive Content,We Are Here For You And Without You And Your Support We Can’t Continue
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