Building a Recommendation System with R

Suresh K. Gorakala, Michele Usuelli

  • 出版商: Packt Publishing
  • 出版日期: 2015-09-30
  • 售價: $1,410
  • 貴賓價: 9.5$1,340
  • 語言: 英文
  • 頁數: 135
  • 裝訂: Paperback
  • ISBN: 1783554495
  • ISBN-13: 9781783554492
  • 相關分類: 推薦系統
  • 海外代購書籍(需單獨結帳)

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商品描述

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.

商品描述(中文翻譯)

學習使用R建立強大且穩健的推薦引擎的藝術

關於本書
- 學習運用各種數據挖掘技術
- 瞭解一些最受歡迎的推薦技術
- 這是一本充滿實例的逐步指南,幫助您建立和優化推薦引擎

本書適合對機器學習和R有一定了解的熟練開發人員,並希望進一步提升技能以構建推薦系統的讀者。

您將學到什麼
- 熟悉推薦的最重要分支
- 瞭解各種數據處理和數據挖掘技術
- 評估和優化推薦算法
- 在構建模型之前準備和結構化數據
- 在R中探索不同的推薦系統及其實現
- 探索在推薦系統中使用的各種評估技術
- 了解R包recommenderlab,並瞭解如何優化它以構建高效的推薦系統

詳細內容
推薦系統通過廣泛的數據分析為用戶生成建議。R最近成為最受歡迎的數據分析程式語言之一。其結構允許您交互式地探索數據,並且由於其廣泛的國際社區,其模組包含最尖端的技術。R語言的這一獨特特點使其成為希望構建推薦系統的開發人員的首選。

本書將幫助您瞭解如何使用R構建推薦系統。它首先解釋了數據挖掘和機器學習的基礎知識。接下來,您將熟悉如何使用R構建和優化推薦模型。然後,您將獲得最受歡迎的推薦技術的概述。最後,您將學習實現本書中學到的所有概念,以構建一個推薦系統。

風格和方法
這是一本逐步指南,將帶您完成一系列核心任務。每個任務都通過實際示例詳細解釋。