End-To-End Data Science With SAS by Gearheart, James -- Read -- Imperial Library of Trantor

Index

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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