Building a Recommendation System with R

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· Packt Publishing Ltd
E‑kniha
158
Počet strán

Táto e‑kniha

Learn the art of building robust and powerful recommendation engines using RAbout This BookLearn to exploit various data mining techniquesUnderstand some of the most popular recommendation techniquesThis is a step-by-step guide full of real-world examples to help you build and optimize recommendation enginesWho This Book Is For

If you are a competent developer with some knowledge of machine learning and R, and want to further enhance your skills to build recommendation systems, then this book is for you.

What You Will LearnGet to grips with the most important branches of recommendationUnderstand various data processing and data mining techniquesEvaluate and optimize the recommendation algorithmsPrepare and structure the data before building modelsDiscover different recommender systems along with their implementation in RExplore various evaluation techniques used in recommender systemsGet to know about recommenderlab, an R package, and understand how to optimize it to build efficient recommendation systemsIn Detail

A recommendation system performs extensive data analysis in order to generate suggestions to its users about what might interest them. R has recently become one of the most popular programming languages for the data analysis. Its structure allows you to interactively explore the data and its modules contain the most cutting-edge techniques thanks to its wide international community. This distinctive feature of the R language makes it a preferred choice for developers who are looking to build recommendation systems.

The book will help you understand how to build recommender systems using R. It starts off by explaining the basics of data mining and machine learning. Next, you will be familiarized with how to build and optimize recommender models using R. Following that, you will be given an overview of the most popular recommendation techniques. Finally, you will learn to implement all the concepts you have learned throughout the book to build a recommender system.

Style and approach

This is a step-by-step guide that will take you through a series of core tasks. Every task is explained in detail with the help of practical examples.

O autorovi

Suresh K. Gorakala is a blogger, data analyst, and consultant on data mining, big data analytics, and visualization tools. Since 2013, he has been writing and maintaining a blog on data science at http://www.dataperspective.info/. Suresh holds a bachelor's degree in mechanical engineering from SRKR Engineering College, which is affiliated with Andhra University, India. He loves generating ideas, building data products, teaching, photography, and travelling. Suresh can be reached at sureshkumargorakala@gmail.com.You can also follow him on Twitter at @sureshgorakala.

Michele Usuelli is a data scientist, writer, and R enthusiast specialized in the fields of big data and machine learning. He currently works for Revolution Analytics, the leading R-based company that got acquired by Microsoft in April 2015. Michele graduated in mathematical engineering and has worked with a big data start-up and a big publishing company in the past. He is also the author of R Machine Learning Essentials, Packt Publishing.

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