【2017新书】Beginning Data Science in R

相似文件 换一批

是 否 +2 论坛币

k人 参与回答

经管之家送您一份

应届毕业生专属福利!

求职就业群

赵安豆老师微信：zhaoandou666

经管之家联合CDA

送您一个全额奖学金名额~ !

立即领取

感谢您参与论坛问题回答

经管之家送您两个论坛币！

+2 论坛币

• Title: Beginning Data Science in R: Data Analysis, Visualization, and Modelling for the Data Scientist
• Author: Thomas Mailund
• Length: 352 pages
• Edition: 1st ed.
• Language: English
• Publisher: Apress
• Publication Date: 2017-04-05
• ISBN-10: 1484226704
• ISBN-13: 9781484226704
  

Apress.Beginning.Data.Science.in.R.1484226704.zip (5.21 MB, 需要: 5 个论坛币) 本附件包括：

• Apress.Beginning.Data.Science.in.R.1484226704.pdf

2017-3-10 10:56:25 上传

需要: 5 个论坛币  [购买]

Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. This book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R.
Beginning Data Science in R details how data science is a combination of statistics, computational science, and machine learning. You’ll see how to efficiently structure and mine data to extract useful patterns and build mathematical models. This requires computational methods and programming, and R is an ideal programming language for this.
This book is based on a number of lecture notes for classes the author has taught on data science and statistical programming using the R programming language. Modern data analysis requires computational skills and usually a minimum of programming.

What You Will Learn

• Perform data science and analytics using statistics and the R programming language
• Visualize and explore data, including working with large data sets found in big data
• Build an R package
• Test and check your code
• Practice version control
• Profile and optimize your code
  

Who This Book Is For

Those with some data science or analytics background, but not necessarily experience with the R programming language.

Table of Contents

Chapter 1: Introduction to R Programming
Chapter 2: Reproducible Analysis
Chapter 3: Data Manipulation
Chapter 4: Visualizing Data
Chapter 5: Working with Large Datasets
Chapter 6: Supervised Learning
Chapter 7: Unsupervised Learning
Chapter 8: More R Programming
Chapter 9: Advanced R Programming
Chapter 10: Object Oriented Programming
Chapter 11: Building an R Package
Chapter 12: Testing and Package Checking
Chapter 13: Version Control
Chapter 14: Profiling and Optimizing

扫码加我 拉你入群

请注明：姓名-公司-职位

以便审核进群资格，未注明则拒绝

分享0 收藏9 回帖

关键词：Data Science Beginning Science beginn begin

感谢分享

谢谢分享

谢谢分享

XIE XIE, A GOOD BOOK IS GOOG.

谢谢分享

感谢分享~~

谢谢分享

并没有看到说明是什麽格式的,不是PDF格式的.