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Building a Recommendation System with R Paperback – September 29, 2015

by Suresh K. Gorakala (Author), Michele Usuelli (Author)

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Learn the art of building robust and powerful recommendation engines using R

About This Book

Learn to exploit various data mining techniques
Understand some of the most popular recommendation techniques
This is a step-by-step guide full of real-world examples to help you build and optimize recommendation engines

Who 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 Learn

Get to grips with the most important branches of recommendation
Understand various data processing and data mining techniques
Evaluate and optimize the recommendation algorithms
Prepare and structure the data before building models
Discover different recommender systems along with their implementation in R
Explore various evaluation techniques used in recommender systems
Get to know about recommenderlab, an R package, and understand how to optimize it to build efficient recommendation systems

In 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.

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Product details

Item Weight : 9.9 ounces
Paperback : 158 pages
ISBN-10 : 1783554495
ISBN-13 : 978-1783554492
Product Dimensions : 7.5 x 0.36 x 9.25 inches
Publisher : Packt Publishing (September 29, 2015)
Language: : English

Best Sellers Rank: #1,934,887 in Books (See Top 100 in Books)
- #566 in Machine Theory (Books)
- #946 in Mathematical & Statistical Software
- #1,795 in Data Processing

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AAA

In-depth resource on building recommender systems in R

Reviewed in the United States on August 8, 2016

Verified Purchase

This is, as far as I know, the only book on the subject of recommender systems in R. The book is a great resource for those interested in building a recommender system in R from the grounds up. The authors start by giving a good overview of the recommender problems with detailed examples, then in the second chapter they cover the techniques used in recommender systems. The last three chapters present the in-depth process of building and evaluating a recommender system in R. Chapter 5 gives a very detailed example of building a recommender system using unstructured data. I would highly recommend this book!

5 people found this helpful

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Brandon Loudermilk

Poorly edited with syntax errors

Reviewed in the United States on May 19, 2016

Verified Purchase

As a software engineer and data scientist, I read a lot of technical books. This one is a poorly executed attempt at explaining how to build recommendation systems in R. The book suffers from syntax errors and poor editing - downloading the dataset required an email because of problems with their [the publisher's] website. The kindle version (at least on kindle cloud reader) does not allow copy/paste -- must manually type to do exercises. This is the last publication I will buy from Packt Publishers, and I will do my best to persuade others to boycott this company. If you want to buy a book on recommendation engines, I would go with "Recommender Systems" by Charu Aggarwal (Springer Press).

6 people found this helpful

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Oleg Okun

Good introduction for beginners

Reviewed in the United States on October 25, 2015

This book provides a good and quick introduction to recommender systems (RS) and implementation details of such systems in R. It starts from basic definitions and an overview of different types of RS, followed by a non-mathematical description of several, most common data mining algorithms that could be used in RS. The R package 'recommenderlab' is discussed in detail, together with numerous R snippets demonstrating the package functionality on the MovieLense database of real recommendations. The important task of RS performance evaluation is given enough space as well as the whole chapter of how to build your own recommendation package based on recommenderlab functions is provided.

Thus, entrants into this field who have basic knowledge of data mining algorithms as well as R may find this book easy to read and understand. However, for more experience users, especially with RS experience, this book might not bring much new information: The important question of how RS perform recommendations when either a product is totally new (there are still no users who reviewed it) or a user doesn't yet have any reviews is only briefly touched.

One person found this helpful

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Abhishek Shivkumar

I think this book makes a very good reference in an academic set up as well

Reviewed in the United States on November 29, 2015

The book provides a complete end-end overview of a recommendation system. I have often come across books and papers that explain only the algorithms but without any reference to the business use case but this book covers all aspects of a recommendation system. I found the data mining algorithms section very interesting which gives a detailed overview of the various algorithms used in a recommendation system. The figures were very clear and all the mathematical explanations were concise. The author also provides the complete code in R and explains all parts of it without making any assumptions. I think this book makes a very good reference in an academic set up as well. The book summarizes everything with a detailed case study on recommendation system which gives the reader a complete overview that puts things into practice. Overall, a great read.

One person found this helpful

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Mary Anne Thygesen

Good companion to Machine Learning

Reviewed in the United States on October 31, 2015

This is a whole book on a topic that is often only a chapter in other books. The example code runs fine. The book has easy to understand examples and directions. A good companion to a machine learning course.

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Barry Higgins

Great introduction to the world of recommendation systems.

Reviewed in the United States on November 16, 2015

This book is great for anyone setting out into the world of Recommendation Systems or anyone who has wondered, where do Amazon and Facebook know what kind of books I would like or that I know that person? Chapters are well laid out and plenty of code examples for the reader to try.

The final chapter walks you through how to build your own RS, which I found very interesting and really brought the whole concept home.

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Eran Raviv

A good case study but not much more.

Reviewed in the United States on November 11, 2015

The book provides a good account of a single case study, but not much more. The first couple of chapters are short, general description of few well rehearsed machine-leaning algorithms. However, if you really want to understand those algorithms you will have to look elsewhere for more elaborate sources, and better sources are abound. As for the recommendation system case study, it is quite detailed and can possibly be adapted to other applications. So if this is the one thing you are after, the book fits.

One person found this helpful

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Top reviews from other countries

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Amazonfreund

Gutes Buch

Reviewed in Germany on December 5, 2015

Verified Purchase

Ein gutes Buch, setzt gute Englischkenntnisse voraus, schade, dass es dieses Buch nicht in deutsch gibt, da sind uns die USA halt immer ein
Stück voraus., Preis ist angemessen, ist für Programmierer mit tiefer gehenden Ambitionen. Alles bestens.

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Oscar

muy buen libro

Reviewed in Mexico on October 19, 2019

Verified Purchase

claro y con buenos ejemplos

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