machinelite 0.0.1

Sci-Lite is Light version of Supervised Machine Learning Model

MachineLite

MachineLite provides a streamlined solution for evaluating various supervised machine learning algorithms, simplifying the data scientist's workflow by automating model integration and evaluation. With just a few lines of code, SciLite enables quick access to essential machine learning evaluations, saving valuable time and effort.

Installation

To install the package, run:

'''bash pip install machinelite '''

Usage

Basic example of how to use the package in Python:

'''bash from machinelite.univariate.regression import Regression as reg result = reg(X_train, X_test, y_train, y_test) print(result) '''

Features

• One-Click Model Integration: Supports easy integration and evaluation of multiple supervised machine learning models, whether for regression or classification.
• Efficient Model Evaluation: Simplifies machine learning model evaluations with standardized output, aiding in faster analysis and comparisons.

Contributing

Contributions to MachineLite are warmly welcomed! If you'd like to contribute, please fork the repository and submit a pull request or open an issue to discuss improvements.

Contact

For any questions or issues, feel free to reach out to:

Author: Ayush Jain Sparsh Email: [e-mail]