# GokuMohandas/Made-With-ML

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## Links

- GitHub: https://github.com/GokuMohandas/Made-With-ML
- Homepage: https://madewithml.com
- awesome-repositories: https://awesome-repositories.com/repository/gokumohandas-made-with-ml.md

## Topics

`data-engineering` `data-quality` `data-science` `deep-learning` `distributed-ml` `distributed-training` `llms` `machine-learning` `mlops` `natural-language-processing` `python` `pytorch` `ray`

## Description

Made-With-ML is an automated documentation generator and developer experience platform designed to transform source code into structured, searchable reference websites. It functions as a codebase intelligence tool that parses implementation details to provide clear explanations of logic and data requirements.

The system distinguishes itself by leveraging language-level type annotations and structured code comments to generate interface specifications. By utilizing static analysis to extract metadata, it automates the transformation of docstrings into web-ready documentation, ensuring that technical references remain synchronized with the underlying codebase.

The platform encompasses a complete pipeline for documentation management, including static site generation and automated deployment to web hosting services. This workflow enables teams to maintain accurate, accessible project knowledge bases that reflect current software specifications and function interfaces.

## Tags

### Content Management & Publishing

- [Documentation Generators](https://awesome-repositories.com/f/content-management-publishing/documentation-generators.md) — Parses source code to produce structured, searchable reference websites.
- [Automated Documentation](https://awesome-repositories.com/f/content-management-publishing/automated-documentation.md) — Generates human-readable technical documentation directly from source code comments.
- [Documentation Publishing](https://awesome-repositories.com/f/content-management-publishing/documentation-publishing.md) — Creates searchable reference websites from code comments and type definitions. ([source](https://madewithml.com/courses/mlops/documentation/))
- [Documentation Hosting](https://awesome-repositories.com/f/content-management-publishing/documentation-hosting.md) — Deploys structured project documentation to web platforms for stakeholder access.

### Development Tools & Productivity

- [Developer Experience Platforms](https://awesome-repositories.com/f/development-tools-productivity/developer-experience-platforms.md) — Automates the creation and deployment of technical documentation from source code.
- [Deployment Automation](https://awesome-repositories.com/f/development-tools-productivity/deployment-automation.md) — Automates the deployment of documentation sites to external hosting services upon code changes.

### Web Development

- [Static Site Builders](https://awesome-repositories.com/f/web-development/static-site-builders.md) — Transforms code comments and metadata into a navigable web-based knowledge base.
- [Static Site Generators](https://awesome-repositories.com/f/web-development/static-site-generators.md) — Compiles documentation files into a searchable collection of interlinked HTML pages.

### Software Engineering & Architecture

- [Type Analysis Tools](https://awesome-repositories.com/f/software-engineering-architecture/type-analysis-tools.md) — Uses language-level type annotations to generate structured interface specifications.
- [Type-Safe Development](https://awesome-repositories.com/f/software-engineering-architecture/type-safe-development.md) — Defines strict data structures to improve maintainability and catch integration errors.
- [Code Intelligence Tools](https://awesome-repositories.com/f/software-engineering-architecture/code-intelligence-tools.md) — Analyzes function signatures to provide explanations of logic and requirements.
- [Interface Definition Tools](https://awesome-repositories.com/f/software-engineering-architecture/interface-definition-tools.md) — Specifies input and output data types to improve code clarity and error detection. ([source](https://madewithml.com/courses/mlops/documentation/))