Issue 5: Build Comprehensive Documentation for AlgoKit! #7
Description
Description:
Create detailed documentation for AlgoKit to help users understand how to utilize the library effectively. The documentation should include installation instructions, usage examples, and descriptions for all modules and functions. It should also provide guidance on contributing to the library for open-source contributors.
Key Features:
Installation Guide: Include instructions for installing AlgoKit via pip or from the source code.
Module Descriptions: Provide detailed explanations of each module, such as Linear Regression, Train-Test Split, and Metrics. Include parameter descriptions, return types, and example usage.
Examples: Include usage examples for common tasks such as training a model, splitting datasets, and evaluating performance using metrics.
Contribution Guide: Add a section on how to contribute to AlgoKit, including setting up a development environment, submitting pull requests, and writing tests.
Where to add:
Create a new docs/ directory at the root of the project. Add a markdown file for each key section, such as:
docs/installation.md
docs/usage.md
docs/contributing.md
docs/api_reference.md
The documentation should eventually be hosted on a platform like Read the Docs or GitHub Pages.