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by James Gearheart
End-to-End Data Science with SAS
Contents
About This Book
About The Author
Chapter 1: Data Science Overview
Introduction to This Book
The Current Data Science Landscape
Introduction to Data Science Concepts
Chapter Review
Chapter 2: Example Step-by-Step Data Science Project
Overview
Business Opportunity
Initial Questions
Get the Data
Select a Performance Measure
Train / Test Split
Target Variable Analysis
Predictor Variable Analysis
Adjusting the TEST Data Set
Building a Predictive Model
Decision Time
Implementation
Chapter Review
Chapter 3: SAS Coding
Overview
Get Data
Explore Data
Manipulate Data
Export Data
Chapter 4: Advanced SAS Coding
Overview
DO Loop
ARRAY Statements
SCAN Function
FIND Function
PUT Function
FIRST. and LAST. Statements
Macros Overview
Macro Variables
Macros
Defining and Calling Macros
Chapter Review
Chapter 5: Create a Modeling Data Set
Overview
ETL
Extract
Data Set
Transform
Load
Chapter Review
Chapter 6: Linear Regression Models
Overview
Regression Structure
Gradient Descent
Linear Regression Assumptions
Linear Regression
Simple Linear Regression
Multiple Linear Regression
Regularization Models
Chapter Review
Chapter 7: Parametric Classification Models
Overview
Classification Overview
Logistic Regression
Visualization
Logistic Regression Model
Linear Discriminant Analysis
Chapter Review
Chapter 8: Non-Parametric Models
Overview
Modeling Data Set
K-Nearest Neighbor Model
Tree-Based Models
Random Forest
Gradient Boosting
Support Vector Machine (SVM)
Neural Networks
Chapter Review
Chapter 9: Model Evaluation Metrics
Overview
General Information
Model Output
Accuracy Statistics
Black-Box Evaluation Tools
Chapter Review
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