devinterview-io/explainable-ai-interview-questions

1. This repository is a content-only knowledge/article repo, not an application codebase.

The only tracked artifact is README.md, which contains a long-form educational article on Explainable AI interview questions.

2. The primary subsystem is the Markdown content itself.

It is structured as a top-level title followed by 35 question/answer sections, each representing a self-contained documentation block.

3. The content is organized as a linear reading experience rather than a modular software system.

There are no source files, packages, services, tests, or build scripts in the repository tree.

4. A second subsystem is embedded media.

The README references externally hosted images via Firebase Storage URLs, including a banner image and at least one diagram image used to illustrate concepts.

5. A third subsystem is outbound navigation to the Devinterview.io site.

The README links to a category page and a dedicated Explainable AI questions page, so the repo acts as a gateway into a larger content platform.

6. The repository’s data flow is simple: Markdown is rendered by whatever host/viewer displays the README, and the viewer pulls external assets on demand.

There is no local asset pipeline; images and linked pages are fetched at read time from third-party infrastructure.

7. The presentation layer is the README rendering environment itself, such as GitHub or a similar Markdown renderer.

All formatting, headings, links, and image display are handled by that host rather than by code in this repo.

8. There is no backend, database, API, authentication, or user state management in this repository.

Any interactive behavior is limited to hyperlink navigation out to external pages.

9. The content domain is machine learning education, specifically explainability concepts such as SHAP, LIME, PDPs, counterfactuals, feature importance, and interpretability trade-offs.

These are all informational sections, not executable modules.

10. For an architecture diagram, this repo should be modeled as a single documentation node with two external dependencies: hosted images and linked web pages.

The important boundary is between local Markdown content and remote content delivery from Firebase Storage and Devinterview.io.

11. Operationally, the repository is static and essentially maintenance-light.

Updates would consist of editing prose, adding/removing sections, or changing external links and images.

12. In short, the architecture is: one Markdown document, rendered by an external viewer, enriched by externally hosted images, and cross-linked to a related knowledge site.

There are no internal service interactions or data-processing pipelines to diagram beyond those external content references.