# Apply for Replit’s first Machine Learning Hackathon Apply for Replit’s first Machine Learning Hackathon **Featured image unavailable: Cover artwork for the article “Apply for Replit’s first Machine Learning Hackathon”.** [Open original](https://replit.com/api/storage/public-objects/article-media/ml-hackathon/sanity-e037d8b40848fb9e8693c12d891ff7296269567a.b3c8e24cfd7b27ec.webp) - Published: 2023-01-11T00:00:00.000Z - Authors: Ornella Altunyan - Canonical: https://replit-engineering-blog.pages.dev/ml-hackathon/ --- **Image unavailable: Hackathon illustration with Replit and Weights & Biases branding, books, and a cable connecting two computers.** [Open original](https://replit.com/api/storage/public-objects/article-media/ml-hackathon/sanity-e037d8b40848fb9e8693c12d891ff7296269567a.b3c8e24cfd7b27ec.webp) We’re extremely excited to announce Replit’s very first Machine Learning Hackathon, in partnership with [Weights and Biases](https://wandb.ai/site)\! If you’re interested in joining the waitlist, head over to the [official site](https://machine-learning-hackathon.replit-community.repl.co/). [Sign up for the Waitlist](https://machine-learning-hackathon.replit-community.repl.co/) Weights and Biases is a machine learning platform that tracks everything you need to make your models reproducible – from hyperparameters and code to model weights and dataset versions. If you’ve never worked with W&B, check out this [example Repl](https://replit.com/@wandb) for an introduction\! The total prize pool is over 500,000 Cycles – there are multiple opportunities to win, with prizes for [Best Weights & Biases Report](https://wandb.ai/wandb/intro/reports/Some-of-our-Favorite-Reports--VmlldzozMTAzNjQ3), Best Repl, an Honorable Mention, and of course, the Grand Prize of 300,000 cycles. ## How do I participate? To start off, you’ll need to register for the waitlist which you can do [here](https://machine-learning-hackathon.replit-community.repl.co/). If selected to participate, you’ll receive an email with all of the details, including access to GPUs and a [Cycles](https://docs.replit.com/cycles/about-cycles) stipend to power your project. Teams and individuals over the age of 13 are eligible to enter, and one entry per person/team is permitted. You’ll need a Replit account, as well as a [Weights & Biases](https://wandb.ai/site) account, to participate. The Machine Learning Hackathon will take place from February 4th to 11th, 2023. On February 4th, join us for the [live opening ceremony](https://www.youtube.com/live/4-yfJgKyCp4?feature=share) where we’ll work through a tutorial, announce the prizes, and review the rules for submission\! To submit your project, you’ll return to the [site](https://machine-learning-hackathon.replit-community.repl.co/) and use the submission form, making sure to select which prizes you wish to compete for\! To be eligible for the Best Replit Project prize, you’ll also need to [publish your work](https://docs.replit.com/hosting/sharing-your-repl) to [Community](https://replit.com/community/all) with the #wandb tag. All projects must be submitted by 11:59PM PST on February 11, 2023. When the hackathon ends and all projects are submitted, the judges have 4 days to choose the winners. The judges will be choosing the winners based on the prize categories listed on the [site](https://machine-learning-hackathon.replit-community.repl.co/). Be sure to tune in to our [closing ceremony livestream](https://www.youtube.com/watch?v=-BP4J1Gno2A) on YouTube on February 15th to hear us announce the winners live\! ## Resources to Get Started If you’re just getting started with your machine learning journey, not to worry – we’ve got plenty of resources to get you setting up your models and making discoveries in no time. We're also hosting Weights & Biases CEO [Lukas Biewald](https://twitter.com/l2k) and our very own [Amjad Masad](https://twitter.com/amasad) for a fireside chat on the future of ML on January 18th, where we'll show off what you can do when you combine the power of W&B and Replit. Join us [live](https://www.youtube.com/watch?v=pFsj9V6-1NE) or watch on-demand anytime on our [YouTube channel](https://www.youtube.com/@replit). ### Weights & Biases Community Resources - [Photo Prediction Repl with Weights & Biases](https://replit.com/@wandb/Photo-Prediction-App) - [Weights & Biases Official Docs](https://docs.wandb.ai/) - [Weights & Biases Community Blog](https://wandb.ai/fully-connected?utm_source=fully_connected&utm_medium=blog&utm_campaign=FC_home&utm_content=Replit) - [Weights & Biases Community Discord](https://wandb.me/discord) - [Example Weights & Biases Reports](https://wandb.ai/wandb/intro/reports/A-Few-of-Our-Favorite-W-B-Reports--VmlldzozMTAzNjQ3) ### Replit Resources - [Python Data Science + GPUs](https://replit.com/@mattiselin/Python-Data-Science-GPU-Enabled) - Torch example - [Tensorflow Demo](https://replit.com/@tobyho/TensorflowGPU)