Companion Library for Springer Book "Applied Data Analysis and Modeling" by T. Agami Reddy and Gregor P. Henze to be found here.
Filling this library is a continuous process. Here is an overview over all notebooks currently in the Library, split between workbooks solving specific problems from the book, and workbooks explaining general concepts.
| Topic | Relevant chapters | Link to workbook |
|---|---|---|
| Central limit theorem | 2 | CLT example |
| Descriptive statistics | 3.4 | Energy grid example |
| ANOVA | 4.3 | ANOVA example |
| Ordinary least squares | 5 | OLS example |
| Karush-Kuhn-Tucker Criteria | 7 | KKT_example |
| Simple LP and MIP optimization | 7.5.5 | python_LP_example |
| Shrinkage methods (Lasso & Ridge) | 9 | Shinkage example |
| Deep neural networks | 11 | Neural Network example |
| Tree based methods | 11 | Tree examples |
| Clustering methods | 11.3 | Clustering examples |
| Support vector regression | 11 | SVR examples |
| Book Problem | Problem Topic | Link to workbook |
|---|---|---|
| 3.7.2 | Uncertainty propagation | Example 3.7.2 |
| 3.12 | Uncertainty propagation | Problem 3.12 |
| 4.4 | Hypothesis testing | Problem 4.4 |
| 4.10 | Hypothesis testing | Problem 4.10 |
| 4.11 | Hypothesis testing | Problem 4.11 |
| 5.1 | Ordinary least squares | Problem 5.1 |
| 5.7 | OLS | Problem 5.7 |
| 5.14 | OLS, indicator variables | Problem 5.14 |
| 7.5.4 | Linear Problems | Example 7.5.4 |
If you have any problems, or have feedback/suggestions/improvement, please contact Tim Diller at tim.diller /(äd)/ eurac.edu