Dagshub
DagsHub simplifies the process of building better models and managing unstructured data projects by consolidating data, code, experiments, and models in one place.
Collect, curate, annotate, visualize, and version your unstructured datasets
Track your experiment
progress, understand trends, and compare results
Manage your models and deployments in one place
Trace your work from the production model, through experiment to the source datasets
Since we started using Dagshub, we have been able to significantly reduce the time it takes to run experiments. With streamlined experiment management and version control capabilities, we can quickly iterate and optimize our models, leading to faster results and more efficient workflows. This has been a game-changer for our team at Mana.bio.
DagsHub has been an integral part of our success. We needed an organized framework for our ML workflows and DagsHub’s philosophy and tools made it the perfect fit. We’ve been using DagsHub for a long time and can’t imagine working on ML projects without it.
As an ML practitioner and instructor DagsHub is pretty amazing. Designed near perfectly for collaborative data science and just as good for teaching. It has integrations with everything you need: GitHub, MLflow, Label Studio, and DVC. Do yourself a favor and check out DagsHub. It has a small learning curve but once you do one project you’ll have a hard time using anything else.
My team can’t stop talking about DagsHub. It’s a tool that truly empowers us to autonomously manage our entire data science projects. DagsHub simplifies the process of ingesting and sharing data for production, making life much easier for our data scientists.
