We’re excited to share that DagsHub is partnering with Hacktoberfest to celebrate its 10th anniversary!

Join us for a month-long celebration of open-source contributions to Machine Learning and AI projects. Gain hands-on experience building datasets, models, pipelines, and more!

From non-code contributors to Binary Sorcerers, everyone is welcome – Check out ways to get involved.

What is Hacktoberfest?

Hacktoberfest is a month-long virtual festival of open source. Participants worldwide, and of all skill levels, give back to the community by contributing to open-source projects. Celebrating its 10th anniversary, Hacktoberfest has contributed 2.35 million pull/merge requests to open-source projects so far!

What is DagsHub?

DagsHub is a centralized platform to host and manage machine learning projects, including code, data, models, experiments, annotations, model registry, and more! DagsHub does the MLOps heavy lifting for its users. Every repository comes with configured S3 storage, an experiment tracking server, and an annotation workspace - all using popular open-source tools like MLflow, DVC, Git, and Label Studio.

How to participate in DagsHub's Machine Learning Challenge during Hacktoberfest?

• Register to DagsHub and Hacktoberfest anytime between September 26 and October 31.
• Choose a project from the list below or any DagsHub hosted project participating in Hacktoberfest (search for projects with the “hacktoberfest” topic).
• Submit pull requests on both DagsHub and GitHub. If it's not a challenge listed below, make sure to open a pull request on our Hacktoberfest Issues project.  
• Your pull requests must be accepted by the project maintainers to count towards your total contributions.

How do you get contributions for your Machine Learning Project?

• Make your repository Hacktoberfest-ready by adding the "hacktoberfest" topic.
• Add the "hacktoberfest" label to issues you'd like contributors to assist with a difficulty level label: "good first issue", "intermediate", "advanced."
• Review pull/merge requests, accepting those that are valid by merging them, leaving an overall approving review, or by adding the "hacktoberfest-accepted" label.
• Find the issue on the Hacktoberfest Issues repository, and mark it with the "hacktoberfest-accepted" label.

What Machine Learning projects participate in Hacktoberfest?

Low to non-code

• Open Source Machine Learning Datasets: Enrich the open-source dataset domain and enhance its accessibility and capabilities by exposing them to DagsHub Data Engine, unlocking unique data management capabilities.
• Open Source Machine Learning Models: Enrich the open-source machine-learning model domain and enhance its accessibility and capabilities for the global machine-learning community.

Beginner

• Contribute 3D Models Datasets: Enrich the 3D Model datasets and make them more accessible. For that, DagsHub added 3D data catalog capabilities to DagsHub! You can now upload 3D Models or motion clips to DagsHub and see, move and diff it!
• Papers with EVERYTHING: Connect repos from GitHub to DagsHub that host reproduced papers from NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, and ECCV, and add their datasets and model's weights to DagsHub Storage.
• Contribute Audio Datasets: Enrich the 3D Model datasets and make them more accessible. For that, DagsHub added Audio capabilities, enabling you to see its spectrogram, wave, and even listen to it! You can see a vivid example of this (extremely cool) feature in our Librispeech-ASR-corpus project.

Intermediate

• Data Pipeline: Build data pipelines using DVC for automation and versioning of Open Source Machine Learning projects.
• Experiment Tracking: Contribute MLflow experiment tracking capabilities to Open Source Machine Learning projects.

Advanced

• General projects: Any Open Source project on DagsHub is open for contribution!
• CheXNet: Keras reimplementation of CheXNet: pathology classification from chest X-Ray images
• DPT: a QA-bot designed to help answer questions about DagsHub. It is a fork of the brilliant buster project.
• Active Learning: A template for an ML Backend that implements a REST API compatible with Label Studio for active learning
• Savta Depth: Monocular Depth Estimation – Turn 2d photos into 3d photos – show your grandma the awesome results.
• Kvasir Image Segmentation: This Project automates a CI/CD pipeline to train an image segmentation model to detect diseases in the GI track.

Does DagsHub provide any special swag?

• The first 10 participants whose initial 10 PR/MR on the Intermediate and Advanced challenges are accepted will get a DagsHub swag package!
• The first 10 participants whose initial 10 PR/MR on the Noe-code and Beginner challenges are accepted will get a DagsHub stickers.

How can I contact the DagsHub team for support?

The DagsHub team (& community) is available 24/7 in the DagsHub Discord server. We ask that questions regarding Hacktoberfest will be asked on DagsHub's Hacktoberfest Discord channel.

I signed up for Hacktoberfest in mid-October. Will pull requests that I created earlier in October count?

Yes, all pull requests created between October 1st and October 31st will count, regardless of when you register for Hacktoberfest. Pull requests created before October 1st but merged or marked as ready for review after do not count. Pull requests still in review after October 31st and meeting the criteria will count towards your completion goal.

The DagsHub team is looking forward to your contributions. Good luck and let us know if we can help!