What is it?

Hacktoberfest is a monthlong celebration of open source software organized by DigitalOcean. The official program page has all the details you need as well as resources for getting started. This page is specifically to aid machine learning developers who want to participate in Hacktoberfest. The goal of the program is to contribute at least four pull requests in the month of October to any public GitHub repositories.

The issues for ML developers?
  • The first repositories that come to mind are TensorFlow, PyTorch, Scikit-learn, etc. but these repositories are often very large and will have very few beginner friendly PR opportunities.
  • Many also have highly optimized code, often in languages that most ML practitioners don't use regularly (C++), which introduces yet another hurdle for contributions.
  • It's difficult to discover active ML repositories on GitHub that are looking for contributions. Most ML work are single update, isolated implementations of research papers or popular architectures.
Our solution

Made With ML is an open, community driven platform where ML developers discover and share their work. Everything is organized by tags and curated by the community. So we can easily identify (and update) the best ML repositories that Hacktoberfest participants can contribute to! Check out the projects below 👇

📚 Resources

Join our Slack channel (and join the #hacktoberfest channel) to ask questions and discuss with other ML developers participating in this year's Hacktoberfest.

  1. Explore beginner-friendly, active ML repositories in our Hacktoberfest collection. You can search (on the right side) by popular topics as well as sort by latest / popular.
  2. You can also discover the best libraries by topic on our auto-updated, community-curated Topics page.
  3. You can also use the search bar located at top on the main navigation bar to search for any topic (beyond our Topics page) and just add the tag `library`.
Table of Contents
📦 Repositories
latest | popular
PyTorch Lightning
The lightweight PyTorch wrapper for ML researchers. Scale your models. Write less boilerplate.
pytorch pytorch-lightning template library
PyTorch CNN Trainer
A simple package to fine-tune CNNs from torchvision and Pytorch Image models by Ross Wightman.
torchvision convolutional-neural-networks pytorch training
Multi-target in Albumentations
Many images, many masks, bounding boxes, and key points. How to transform them in sync?
data-augmentation image-augmentation computer-vision albumentations
Simple Transformers
Transformers for Classification, NER, QA, Language Modeling, Language Generation, T5, Multi-Modal, and Conversational AI.
transformers named-entity-recognition question-answering language-modeling
DeText: A Deep Neural Text Understanding Framework
DeText: A Deep Neural Text Understanding Framework for Ranking and Classification Tasks.
natural-language-processing natural-language-understanding detext code
Lightweight Python library for adding real-time 2D object tracking to any detector.
object-tracking norfair computer-vision code
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