Building a Recommendation System with R
暫譯: 使用 R 建立推薦系統
Suresh K. Gorakala, Michele Usuelli
- 出版商: Packt Publishing
- 出版日期: 2015-09-30
- 售價: $1,460
- 貴賓價: 9.5 折 $1,387
- 語言: 英文
- 頁數: 135
- 裝訂: Paperback
- ISBN: 1783554495
- ISBN-13: 9781783554492
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相關分類:
推薦系統
海外代購書籍(需單獨結帳)
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相關主題
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 建立穩健且強大的推薦引擎的藝術
本書介紹
- 學習利用各種資料探勘技術
- 了解一些最受歡迎的推薦技術
- 這是一本逐步指導的書籍,充滿了實際案例,幫助您建立和優化推薦引擎
本書適合誰閱讀
如果您是一位具備一定機器學習和 R 知識的開發者,並希望進一步提升技能以建立推薦系統,那麼這本書適合您。
您將學到什麼
- 掌握推薦的最重要分支
- 了解各種資料處理和資料探勘技術
- 評估和優化推薦演算法
- 在建立模型之前準備和結構化資料
- 探索不同的推薦系統及其在 R 中的實作
- 研究推薦系統中使用的各種評估技術
- 了解 recommenderlab 這個 R 套件,並理解如何優化它以建立高效的推薦系統
詳細內容
推薦系統進行廣泛的資料分析,以便為用戶生成可能感興趣的建議。R 最近成為資料分析中最受歡迎的程式語言之一。其結構允許您互動式地探索資料,其模組因其廣泛的國際社群而包含最前沿的技術。R 語言的這一獨特特性使其成為尋求建立推薦系統的開發者的首選。
本書將幫助您了解如何使用 R 建立推薦系統。它首先解釋資料探勘和機器學習的基本概念。接下來,您將熟悉如何使用 R 建立和優化推薦模型。隨後,您將獲得最受歡迎的推薦技術的概述。最後,您將學會實作整本書中學到的所有概念,以建立一個推薦系統。
風格與方法
這是一本逐步指導的書籍,將帶您完成一系列核心任務。每個任務都詳細解釋,並輔以實際範例。