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• Cover
• Introduction
• About This Book
• Foolish Assumptions
• Icons Used in This Book
• Beyond the Book
• Where to Go from Here
• Part 1: Getting Started with Predictive Analytics
• Chapter 1: Entering the Arena
• Exploring Predictive Analytics
• Adding Business Value
• Starting a Predictive Analytic Project
• Ongoing Predictive Analytics
• Forming Your Predictive Analytics Team
• Surveying the Marketplace
• Chapter 2: Predictive Analytics in the Wild
• Online Marketing and Retail
• Implementing a Recommender System
• Target Marketing
• Personalization
• Content and Text Analytics
• Chapter 3: Exploring Your Data Types and Associated Techniques
• Recognizing Your Data Types
• Identifying Data Categories
• Generating Predictive Analytics
• Connecting to Related Disciplines
• Chapter 4: Complexities of Data
• Finding Value in Your Data
• Constantly Changing Data
• Complexities in Searching Your Data
• Differentiating Business Intelligence from Big-Data Analytics
• Exploration of Raw Data
• Part 2: Incorporating Algorithms in Your Models
• Chapter 5: Applying Models
• Modeling Data
• Healthcare Analytics Case Studies
• Social and Marketing Analytics Case Studies
• Prognostics and its Relation to Predictive Analytics
• The Rise of Open Data
• Chapter 6: Identifying Similarities in Data
• Explaining Data Clustering
• Converting Raw Data into a Matrix
• Identifying Groups in Your Data
• Finding Associations in Data Items
• Applying Biologically Inspired Clustering Techniques
• Chapter 7: Predicting the Future Using Data Classification
• Explaining Data Classification
• Introducing Data Classification to Your Business
• Exploring the Data-Classification Process
• Using Data Classification to Predict the Future
• Ensemble Methods to Boost Prediction Accuracy
• Deep Learning
• Part 3: Developing a Roadmap
• Chapter 8: Convincing Your Management to Adopt Predictive Analytics
• Making the Business Case
• Gathering Support from Stakeholders
• Presenting Your Proposal
• Chapter 9: Preparing Data
• Listing the Business Objectives
• Processing Your Data
• Working with Features
• Structuring Your Data
• Chapter 10: Building a Predictive Model
• Getting Started
• Developing and Testing the Model
• Going Live with the Model
• Chapter 11: Visualization of Analytical Results
• Visualization as a Predictive Tool
• Evaluating Your Visualization
• Visualizing Your Model’s Analytical Results
• Novel Visualization in Predictive Analytics
• Big Data Visualization Tools
• Part 4: Programming Predictive Analytics
• Chapter 12: Creating Basic Prediction Examples
• Installing the Software Packages
• Preparing the Data
• Making Predictions Using Classification Algorithms
• Chapter 13: Creating Basic Examples of Unsupervised Predictions
• Getting the Sample Dataset
• Using Clustering Algorithms to Make Predictions
• Chapter 14: Predictive Modeling with R
• Programming in R
• Making Predictions Using R
• Chapter 15: Avoiding Analysis Traps
• Data Challenges
• Analysis Challenges
• Part 5: Executing Big Data
• Chapter 16: Targeting Big Data
• Major Technological Trends in Predictive Analytics
• Applying Open-Source Tools to Big Data
• Chapter 17: Getting Ready for Enterprise Analytics
• Analytics as a Service
• Preparing for a Proof-of-Value of Predictive Analytics Prototype
• Part 6: The Part of Tens
• Chapter 18: Ten Reasons to Implement Predictive Analytics
• Identifying Business Goals
• Knowing Your Data
• Organizing Your Data
• Satisfying Your Customers
• Reducing Operational Costs
• Increasing Returns on Investments (ROI)
• Gaining Rapid Access to Information
• Making Informed Decisions
• Gaining Competitive Edge
• Improving the Business
• Chapter 19: Ten Steps to Build a Predictive Analytic Model
• Building a Predictive Analytics Team
• Setting the Business Objectives
• Preparing Your Data
• Sampling Your Data
• Avoiding “Garbage In, Garbage Out”
• Creating Quick Victories
• Fostering Change in Your Organization
• Building Deployable Models
• Evaluating Your Model
• Updating Your Model
• About the Authors
• Connect with Dummies
• End User License Agreement