Metadata-Version: 2.1
Name: machine-learning-with-graph
Version: 0.0.1
Summary: A comprehensive package for graph-based machine learning algorithms.
Home-page: https://github.com/yourusername/machine-learning-with-graph
Author: Susheel Gounder and Parikshit Urs
Author-email: susheelg1107@gmail.com
License: MIT
Project-URL: Bug Reports, https://github.com/susheelg1197/machine-learning-with-graph/issues
Project-URL: Source, https://github.com/susheelg1197/machine-learning-with-graph
Keywords: graph neural networks machine learning GNN GCN GAT
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: networkx
Requires-Dist: torch
Requires-Dist: dgl

# Machine Learning with Graphs Library

This package provides a comprehensive suite of graph-based machine learning algorithms, encapsulated in an easy-to-use Python library.

## Features

- Graph Neural Networks (GNNs) including GCNs, GATs, and more.
- Graph clustering algorithms such as Spectral Clustering and Louvain method.
- Graph embedding methods like Node2Vec and DeepWalk.
- And many other graph-based algorithms.

## Installation

To install the package, run the following command:

```bash
pip install machine_learning_with_graph
