Business Analytics and SQL Essentials
An Overview of Practical Skills for CRISP-DM
- Foreword: Why Data Science?
- Chapter 1: Introduction to Business Analytics
- Chapter 2: AI in Business
- Chapter 3: Databases
- Chapter 4: Data Storage (ERD)
- Chapter 5: Data Retrieval (SQL)
- Chapter 6: Data Project Methodology
- Chapter 7: Introduction to Tableau
- Chapter 8: Exploratory Data Analysis in Tableau
- Chapter 9: Modeling in Excel
- Chapter 10: ML Studio: Introduction to Pipelines
- Chapter 11: ML Studio: Data Cleaning and Preparation
- Chapter 12: ML Studio: Algorithm Selection
- Chapter 13: ML Studio: Selecting the Features
- Chapter 14: ML Studio: Optimizing Model Fit and Performance
- Chapter 15: ML Studio: Natural Language Processing
- Chapter 16: ML Studio: Recommendation Engines
- Chapter 17: Project: Putting It All Together
- Supplement: Datasets
- Supplement: Computer Vision (in progress)