Skip to content

This repository serves as an educational resource for students and enthusiasts in the field of AI and Machine Learning.

Notifications You must be signed in to change notification settings

sousamaf/PyParallelAI

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

6 Commits
 
 
 
 
 
 

Repository files navigation

PyParallelAI

Welcome to PyParallelAI, a resourceful repository dedicated to exploring concurrent and parallel programming techniques in Python, specifically tailored for applications in Artificial Intelligence and Machine Learning.

Overview

This repository serves as an educational resource for students and enthusiasts in the field of AI and Machine Learning. It focuses on demonstrating the practical aspects of concurrent and parallel programming in Python, a critical skill set for optimizing AI algorithms and processes.

Contents

  • Concurrent Programming Examples: Examples demonstrating basic to advanced concepts of concurrent programming in Python.
  • Parallel Programming Tutorials: Step-by-step guides and code snippets for parallel programming, tailored for AI applications.
  • Machine Learning Case Studies: Real-world scenarios where concurrent and parallel programming techniques significantly enhance ML model performance.
  • Best Practices: Tips and tricks for effective and efficient programming in the context of AI.

Getting Started

To get started with the repository:

  1. Clone the Repository:
    git clone https://github.com/sousamaf/PyParallelAI.git
    
  2. Navigate to the Repository:
    cd PyParallelAI
    
  3. Explore the Folders: Each folder is structured to guide you through different concepts and applications.

Contribution

We encourage contributions! If you have suggestions, corrections, or content to add, please submit a pull request or open an issue. Make sure to follow the contribution guidelines outlined in CONTRIBUTING.md.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

  • A special thanks to all contributors and educators in the field of AI and concurrent/parallel programming.
  • This repository is a part of the educational material for AI at Unitins.

About

This repository serves as an educational resource for students and enthusiasts in the field of AI and Machine Learning.

Resources

Contributing

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published