End-to-End Data Science with SAS

End-to-End Data Science with SAS

by James Gearheart
Released June 2020
Publisher(s): SAS Institute
ISBN: 9781642958065

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Book description

Learn data science concepts with real-world examples in SAS!

End-to-End Data Science with SAS: A Hands-On Programming Guide provides clear and practical explanations of the data science environment, machine learning techniques, and the SAS programming knowledge necessary to develop machine learning models in any industry. The book covers concepts including understanding the business need, creating a modeling data set, linear regression, parametric classification models, and non-parametric classification models. Real-world business examples and example code are used to demonstrate each process step-by-step.

Although a significant amount of background information and supporting mathematics are presented, the book is not structured as a textbook, but rather it is a user’s guide for the application of data science and machine learning in a business environment. Readers will learn how to think like a data scientist, wrangle messy data, choose a model, and evaluate the model’s effectiveness. New data scientists or professionals who want more experience with SAS will find this book to be an invaluable reference. Take your data science career to the next level by mastering SAS programming for machine learning models.

Table of contents

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

Product information

  • Title: End-to-End Data Science with SAS
  • Author(s): James Gearheart
  • Release date: June 2020
  • Publisher(s): SAS Institute
  • ISBN: 9781642958065