F# for Machine Learning Essentials

F# for Machine Learning Essentials

EnglishEbook
Mukherjee, Sudipta
Packt Publishing
EAN: 9781783989355
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Detailed information

Get up and running with machine learning with F# in a fun and functional wayKey FeaturesDesign algorithms in F# to tackle complex computing problemsBe a proficient F# data scientist using this simple-to-follow guideSolve real-world, data-related problems with robust statistical models, built for a range of datasetsBook DescriptionThe F# functional programming language enables developers to write simple code to solve complex problems. With F#, developers create consistent and predictable programs that are easier to test and reuse, simpler to parallelize, and are less prone to bugs. If you want to learn how to use F# to build machine learning systems, then this is the book you want. Starting with an introduction to the several categories on machine learning, you will quickly learn to implement time-tested, supervised learning algorithms. You will gradually move on to solving problems on predicting housing pricing using Regression Analysis. You will then learn to use Accord.NET to implement SVM techniques and clustering. You will also learn to build a recommender system for your e-commerce site from scratch. Finally, you will dive into advanced topics such as implementing neural network algorithms while performing sentiment analysis on your data.What you will learnUse F# to find patterns through raw dataBuild a set of classification systems using Accord.NET, Weka, and F#Run machine learning jobs on the Cloud with MBracePerform mathematical operations on matrices and vectors using Math.NETUse a recommender system for your own problem domainIdentify tourist spots across the globe using inputs from the user with decision tree algorithmsWho this book is forIf you are a C# or an F# developer who now wants to explore the area of machine learning, then this book is for you. Familiarity with theoretical concepts and notation of mathematics and statistics would be an added advantage.]]>
EAN 9781783989355
ISBN 1783989351
Binding Ebook
Publisher Packt Publishing
Publication date February 25, 2016
Language English
Country United Kingdom
Authors Mukherjee, Sudipta
Manufacturer information
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