English
资源说明：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.
Table of Contents
Chapter 1: Getting Started with Recommender Systems
Chapter 2: Data Mining Techniques Used in Recommender Systems
Chapter 3: Recommender Systems
Chapter 4: Evaluating the Recommender Systems
Chapter 5: Case Study – Building Your Own Recommendation Engine
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