Hello and welcome to the DagsHub Challenge! 👋

We are very excited to sponsor BoilerMake X Hackathon and see all the amazing projects you’re about to build and share with the world!

Sign up for DagsHub

What is DagsHub?

DagsHub is where people build data science projects. A centralized place to host, version, and manage code, data, models, experiments, and more. It allows you and your team to easily share, review, and reuse work, providing a GitHub experience for machine learning.

How does DagsHub work?

DagsHub is built on popular open-source tools and formats, making it easy to integrate with the tools you already use. For example, we use Git and DVC to version control all project components (code, data, models, artifacts, etc.), MLflow for experiment tracking, model registry and deployment, and Label Studio to improve the annotation workflow.

Getting started with what you need is easy. No need to set up servers or add complicated cloud permissions, DagsHub does the DevOps heavy lifting for you. Learn more about how we're doing it in the video below 👇

https://www.youtube.com/embed/K3r9AXddrRU

How to participate in the challenge?

The challenge is open to all participants of the Hackathon.

To be eligible to enter the challenge, participants must host their project on DagsHub, version their code with Git, their data and models with DVC, and track their experiments with MLflow. This is the only requirement for entry into the challenge. ****

Logistics requirements [IMPORTANT]:

• Make sure to sign up for DagsHub from this link.
• Fill this form with the team’s details so we will add you as a team under purdue-boilermake organization.

How will your project be evaluated?

Once entered, participants' projects will be evaluated based on the following criteria:

1. Reproducibility: This criterion assesses the ease with which the project can be reproduced by others. It involves the use of version control and experiment tracking, dependencies encapsulation (package requirements, OS-level dependencies, etc.), and detailed documentation and/or README file.
2. Difficulty level: the level of interest and challenge provided by the project. It takes into consideration the level of creativity and originality of the project, the level of difficulty involved in the implementation, and the level of interest that the project generates.