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Introduction
Jeremiah Green
1. Data analysis: purposes and applications
2. Accounting Data
3. Data Analysis Applications in Accounting
4. Storytelling with data
5. General Purpose Software - R Basics
6. Data manipulation
7. Visualizing Data
8. Understanding Data with Statistics
9. Data preparation
10. Introduction to Modeling
11. AutoML with Binary Dependent Variables
12. AutoML with Continous Dependent Variables
13. Unsupervised models: clustering and anomaly detection
14. Unsupervised models: principal components
15. Supervised models: parametric models
16. Supervised Models: Tree based methods
17. Supervised Models: Neural networks
18. Text data foundations
19. Large language models
Appendix
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Data Analytics with Accounting Data and R Copyright © by Jeremiah Green. All Rights Reserved.
