Feature description

Proposal: Add support for federated learning within the machine learning submodules. Federated learning is an important paradigm for distributed machine learning, allowing algorithms to be trained across multiple devices or servers holding local data samples, without exchanging them.

This addition could include:

• A brief introduction and documentation about federated learning
• Implementation of basic federated averaging algorithm
• Example usage and integration with existing ML modules
• Tests and sample scripts demonstrating federated learning

This would improve the repository's coverage of modern machine learning techniques and provide educational value for users interested in privacy-preserving distributed learning.