舉報(bào) 
會員
Introduction to R for Business Intelligence
Thisbookisfordataanalysts,businessanalysts,datascienceprofessionalsoranyonewhowantstolearnanalyticapproachestobusinessproblems.BasicfamiliaritywithRisexpected.
目錄(67章)
倒序
- 封面
- 版權(quán)頁
- Credits
- About the Author
- Acknowledgement
- About the Reviewers
- www.PacktPub.com
- eBooks discount offers and more
- Preface
- What this book covers
- What you need for this book
- Who this book is for
- Conventions
- Reader feedback
- Customer support
- Chapter 1. Extract Transform and Load
- Understanding big data in BI analytics
- Extracting data from sources
- Transforming data to fit analytic needs
- Loading data into business systems for analysis
- Summary
- Chapter 2. Data Cleaning
- Summarizing your data for inspection
- Finding and fixing flawed data
- Converting inputs to data types suitable for analysis
- Adapting string variables to a standard
- Summary
- Chapter 3. Exploratory Data Analysis
- Understanding exploratory data analysis
- Analyzing a single data variable
- Analyzing two variables together
- Exploring multiple variables simultaneously
- Summary
- Chapter 4. Linear Regression for Business
- Understanding linear regression
- Checking model assumptions
- Using a simple linear regression
- Refining data for simple linear regression
- Introducing multiple linear regression
- Summary
- Chapter 5. Data Mining with Cluster Analysis
- Explaining clustering analysis
- Partitioning using k-means clustering
- Clustering using hierarchical techniques
- Summary
- Chapter 6. Time Series Analysis
- Analyzing time series data with linear regression
- Introducing key elements of time series analysis
- Building ARIMA time series models
- Summary
- Chapter 7. Visualizing the Datas Story
- Visualizing data
- Plotting with ggplot2
- Geo-mapping using Leaflet
- Creating interactive graphics using rCharts
- Summary
- Chapter 8. Web Dashboards with Shiny
- Creating a basic Shiny app
- Creating a marketing-campaign Shiny app
- Deploying your Shiny app
- Summary
- Appendix A. References
- Appendix B. Other Helpful R Functions
- Chapter 1 - Extract Transform and Load
- Chapter 2 - Data Cleaning
- Appendix C. R Packages Used in the Book
- Appendix D. R Code for Supporting Market Segment Business Case Calculations 更新時(shí)間：2021-08-20 10:34:48
推薦閱讀
- 自動控制工程設(shè)計(jì)入門
- Word 2000、Excel 2000、PowerPoint 2000上機(jī)指導(dǎo)與練習(xí)
- Python Artificial Intelligence Projects for Beginners
- 走入IBM小型機(jī)世界
- 機(jī)器學(xué)習(xí)與大數(shù)據(jù)技術(shù)
- 數(shù)控銑削（加工中心）編程與加工
- Supervised Machine Learning with Python
- Ceph：Designing and Implementing Scalable Storage Systems
- 精通數(shù)據(jù)科學(xué)算法
- Deep Reinforcement Learning Hands-On
- 單片機(jī)C語言程序設(shè)計(jì)完全自學(xué)手冊
- 貫通開源Web圖形與報(bào)表技術(shù)全集
- 基于人工免疫原理的檢測系統(tǒng)模型及其應(yīng)用
- 貫通Java Web輕量級應(yīng)用開發(fā)
- 機(jī)器人剛?cè)狁詈蟿恿W(xué)
- 工廠電氣控制設(shè)備
- 實(shí)戰(zhàn)突擊
- 微計(jì)算機(jī)原理及應(yīng)用
- fastText Quick Start Guide
- 我的IT世界
- 單片機(jī)與微機(jī)原理及應(yīng)用
- Mastering Kubernetes
- S7-200系列PLC應(yīng)用技術(shù)
- IBM主機(jī)技術(shù)一本通
- Mastering PostgreSQL 10
- 自動化焦慮癥：科技與職場的未來（《經(jīng)濟(jì)學(xué)人》選輯）
- R Web Scraping Quick Start Guide
- jQuery即學(xué)即用
- Web應(yīng)用項(xiàng)目開發(fā)
- 移動機(jī)器人導(dǎo)航定位技術(shù)
