This GitHub repo contains notebook examples from "A Practical Overview of Interpretable Machine Learning" blog post. In these examples, we will apply cutting-edge interpretability approaches to tackle problems involving various data types. Few of them are the following:
| Description | Related Data | Link |
|---|---|---|
| Example 1 | Tabular |  |
| Example 2 | Textual | |
| Example 3 | Images | |
| Example 4 | Time Series | |
See our LICENSE for more details.