Hands-On Data Science with R: Execute machine learning and deep learning algorithms, predictive analysis, Markovian methods with R (實戰數據科學:使用 R 執行機器學習、深度學習演算法、預測分析及馬可夫方法)
Vitor Bianchi Lanzetta, Nataraj Dasgupta, Ricardo Anjoleto Farias
- 出版商: Packt Publishing
- 出版日期: 2018-11-30
- 售價: $1,810
- 貴賓價: 9.5 折 $1,720
- 語言: 英文
- 頁數: 420
- 裝訂: Paperback
- ISBN: 1789139406
- ISBN-13: 9781789139402
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相關分類:
R 語言、Machine Learning、DeepLearning、Algorithms-data-structures、Data Science
海外代購書籍(需單獨結帳)
相關主題
商品描述
Practical examples for professionals using R in Data science
Key Features
- Accessible to readers without a background in data science
- Practical and engaging from start to finish, unlock the world of Data Science using real world examples
- Explore machine learning algorithms, predictive analysis, markovian methods and deep learning algorithms with R
Book Description
R being the most widely used programming language when used with data science can be a powerful combination to solve complexities involved with varied data sets in the real world. Data Science with R aims to teach you how to begin performing data science tasks by taking advantage of R's powerful ecosystem of packages. The best way to learn is to play with the data but with a go-to guide while doing so. This will be easiest, practical book in the market that covers the entire data science ecosystem for an aspiring data scientist. The book will take you from the zero to the level where you would be confident to work practically on a data science problem.
The book starts with an introduction to data science and introduces the readers to the R programming language. You will be up and running with R by the end of the first chapter and would have a few basic programs to start their journey. Moving ahead, this book will cover all the important process in data science such as data gathering followed by cleaning the dirtiest data as available and discovering patterns out of it. It gets even more interesting once we start discovering patterns in the 'tidy' data set start applying algorithms to it. You will explore algorithms such as - machine learning algorithms, predictive analysis and finally covering deep learning algorithms.
Till this point in the book, you must have gained fair understanding of the entire ecosystem of data science and you are now all set to develop your data products using R. This is what the next chapter will help you do and did I mention with top of the world visualizations! You will work with the most powerful visualization packages as available in R to ensure your data speaks a story nothing less than a pro.
Towards the end, you will learn how to integrate R with Spark & Hadoop for Large Scale Data Analytics and take it a step further on Cloud.
What You Will Learn
- Understand R programming language and its ecosystem of packages for data science
- Learn the correct approach before solving a problem
- Obtain and clean data before processing
- Master the the essential exploratory techniques for summarizing data
- Examine various Machine Learning prediction models
- Explore the H2O analytics platform in 'R' for Deep learning
- Apply data mining techniques to the available datasets
- Work with interactive visualization packages in R
- Latch onto the right approach to build data products
- Integrate R with Spark & Hadoop for Large Scale Data Analytics
- Take R on Cloud
Who This Book Is For
This book is intended for data analysts and aspiring data scientists with little to no grounding in the fundamentals of data science with R. Basic background in statistics and computational mathematics would be beneficial but is not essential. Basic experience with the R language is assumed.
商品描述(中文翻譯)
《實用範例:使用R進行資料科學的專業人士》
主要特點
- 適合沒有資料科學背景的讀者
- 從頭到尾實用且引人入勝,使用真實世界的範例解鎖資料科學的世界
- 使用R探索機器學習演算法、預測分析、馬可夫方法和深度學習演算法
書籍描述
當R與資料科學結合時,R成為最廣泛使用的程式語言,可以解決現實世界中各種資料集所涉及的複雜性。《使用R進行資料科學》旨在教授如何利用R強大的套件生態系統開始執行資料科學任務。學習的最佳方式是與資料互動,但同時需要一本指南。這本書是市場上最簡單、實用的書籍,涵蓋了整個資料科學生態系統,適合有志成為資料科學家的人。本書將帶領您從零開始,直到您能夠自信地解決資料科學問題。
本書以介紹資料科學和R程式語言為開始。在第一章結束時,您將能夠使用R並具備一些基本程式,開始您的學習之旅。接下來,本書將涵蓋資料科學中的所有重要過程,例如資料收集、清理最骯髒的資料以及發現其中的模式。當我們開始在“整潔”的資料集中發現模式並應用演算法時,事情變得更有趣。您將探索機器學習演算法、預測分析,最後涵蓋深度學習演算法。
到目前為止,您應該對整個資料科學生態系統有了相當的了解,現在可以使用R開發您的資料產品了。下一章將幫助您實現這一目標,而且我提到了世界頂尖的視覺化!您將使用R中最強大的視覺化套件來確保您的資料傳達的是一個專業的故事。
最後,您將學習如何將R與Spark和Hadoop集成,進行大規模資料分析,並在雲端上更進一步。
您將學到什麼
- 了解R程式語言及其資料科學套件生態系統
- 在解決問題之前學習正確的方法
- 在處理資料之前獲取並清理資料
- 掌握摘要資料的基本探索技術
- 檢查各種機器學習預測模型
- 在R中探索H2O分析平台進行深度學習
- 應用資料採礦技術於可用資料集
- 使用R中的互動式視覺化套件
- 掌握建立資料產品的正確方法
- 將R與Spark和Hadoop集成進行大規模資料分析
- 將R應用於雲端
本書適合對象
本書適合沒有資料科學基礎的資料分析師和有志成為資料科學家的人。具備統計和計算數學的基本背景將有所幫助,但不是必需的。假設您具備基本的R語言使用經驗。