Metadata-Version: 2.1
Name: that-ml-library
Version: 0.0.4
Summary: A useful package for EDA and quick ML model building
Home-page: https://github.com/anhquan0412/that-ml-library
Author: Quan Tran
Author-email: anhquan0412@gmail.com
License: Apache Software License 2.0
Keywords: nbdev jupyter notebook python
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: License :: OSI Approved :: Apache Software License
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Provides-Extra: dev
License-File: LICENSE

# that-ml-library

<!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->

## Install

``` sh
pip install that_ml_library
```

For tree visualization function
([`plot_tree_dtreeviz`](https://anhquan0412.github.io/that-ml-library/chart_plotting.html#plot_tree_dtreeviz)
or
[`plot_tree_sklearn`](https://anhquan0412.github.io/that-ml-library/chart_plotting.html#plot_tree_sklearn)),
you also need to install `graphviz`. Please follow the instruction
[here](https://github.com/parrt/dtreeviz#installation)

## How to use

Please visit <https://anhquan0412.github.io/that-ml-library/> for
tutorials and documentations

## A word of caution

This library should only be utilized solely for developing a proof of
concept or prototype for your machine learning model with your specific
dataset, with the aim of evaluating the model’s performance and
interpretability. For deployment in a production environment, opt for a
more organized methodology, such as
<https://scikit-learn.org/stable/modules/compose.html#pipeline>
