Metadata-Version: 2.4
Name: quicklearnkit
Version: 0.4.2
Summary: Learning-first machine learning utilities library for simplified imports, sampling, splitting, and probabilistic preprocessing.
Author: Hazi Afrid
License: MIT License
        
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Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: scikit-learn
Requires-Dist: xgboost
Requires-Dist: seaborn
Requires-Dist: matplotlib
Dynamic: license-file


# QuickLearnKit

[![PyPI version](https://img.shields.io/pypi/v/quicklearnkit.svg)](https://pypi.org/project/quicklearnkit/)
![Python](https://img.shields.io/badge/python-%3E%3D3.8-blue)
[![Documentation Status](https://readthedocs.org/projects/quicklearnkit/badge/?version=latest)](https://quicklearnkit.readthedocs.io/en/latest/)
![License](https://img.shields.io/badge/license-MIT-green)

QuickLearnKit is a **learning-first machine learning utilities library** designed to simplify common ML workflows while preserving full control for advanced users.

It provides:

- Simplified model imports  
- Sampling and dataset utilities  
- Train–test splitting  
- Probabilistic, group-aware imputation  
- Teaching-friendly visualization wrappers  
- Notebook → Script pipeline compilation  

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## Installation

```bash
pip install quicklearnkit
````

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## Documentation

Full documentation is available at:

👉 [https://quicklearnkit.readthedocs.io/en/latest/](https://quicklearnkit.readthedocs.io/en/latest/)

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## Philosophy

> Remove mechanical friction so students can focus on concepts, not syntax.

QuickLearnKit bridges:

Learning → Experimentation → Structured building

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## License

MIT License
