## Installation
To install the package, run the following command:
pip install pygeine
## Educational Modules
to use a function or project explaination just import the function like this :
from pygeine.pybasics import calculator , receipt
## plot module
The plot module provides a set of interactive visualization tools for exploring data using popular machine learning algorithms. It includes functions for plotting scatter plots, confusion matrices, and classification reports for various classification models, such as random forests and support vector machines. The module also provides interactive widgets for adjusting model parameters, such as the number of estimators in a random forest. The visualizations can be customized with different colors and labels to better understand the model's performance.
## Downloading a Project
if you need to download the Actual code for any projects just import the project name and add (_download) like this :
from pygeine.pybasics calculator_download , receipt_download
## Example Notebook
Check out this [Google Colab notebook](https://colab.research.google.com/drive/187SFw4QkZcxVflUlzIH3SMF8ep6kE9L-?usp=sharing) for an example of how to use the functions in this package.
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"description": "\n\n\n## Installation\n\nTo install the package, run the following command:\n\npip install pygeine\n\n\n## Educational Modules\n\nto use a function or project explaination just import the function like this :\n\nfrom pygeine.pybasics import calculator , receipt\n\n## plot module\n\nThe plot module provides a set of interactive visualization tools for exploring data using popular machine learning algorithms. It includes functions for plotting scatter plots, confusion matrices, and classification reports for various classification models, such as random forests and support vector machines. The module also provides interactive widgets for adjusting model parameters, such as the number of estimators in a random forest. The visualizations can be customized with different colors and labels to better understand the model's performance.\n\n## Downloading a Project \n\nif you need to download the Actual code for any projects just import the project name and add (_download) like this :\n\nfrom pygeine.pybasics calculator_download , receipt_download\n\n\n## Example Notebook\n\nCheck out this [Google Colab notebook](https://colab.research.google.com/drive/187SFw4QkZcxVflUlzIH3SMF8ep6kE9L-?usp=sharing) for an example of how to use the functions in this package.\n",
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