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User profile and more
DATA ENGINE
EnrichAnnotateCurateVisualizeVersionStreamMaster
your unstructured data, build reliable models.
Supercharge your production datasets by using a central platform to effectively manage data, metadata, labels, and predictions. Curate data with a pandas-like interface, review & fix problems with your data and labels, and stream it straight to your training pipelines easily.
Every day, machine learning teams battle with the complexity of working on production data
Machine Learning teams face the daily challenge of handling complex production data. They receive vast amounts of information, selecting the most relevant data points, identifying underperforming models, preparing the data for training, conducting experiments, and deploying the best-performing model. It’s a tough battle, but they persist.
Meet Data Engine, the holistic solution for your machine learning datasets
In today’s data-driven world, organizational success hinges on effective data management. By prioritizing data, Data Engine empowers machine learning teams to build better models by providing them with a centralized platform to effectively manage and leverage their datasets. With improved access to high-quality data, machine learning teams can enhance the accuracy and performance of their models, leading to more reliable and impactful results.
Build reliable models with these capabilities
Create task oriented high quality datasets
Curate data using pandas-like syntax based on metadata and annotations. Avoid duplicates and make subsets accessible to all team members.
Visualize unstructured dataset
Go beyond statistics and visualize your actual data with DagsHub. Understand changes over time and gain insights into unstructured datasets.
Evaluate real world data quality
Handle large-scale, ever-changing data with ease. Review and evaluate new data, annotations, and metadata. Modify, communicate, and append samples to different datasets with a click of a button.
Data & model lineage
Track relationships between models and the datasets, annotations, and metadata they were trained on. Ensure reproducibility and gain insights into the evolution of your ML projects.
Hard example mining
Uncover biases and inconsistent annotations. Log model predictions and leverage smart metadata querying. Visualize subsets, predictions, and annotations for informed model decision-making.
Labeling and auto-labeling
Efficiently annotate data with a click. Send subsets to an annotation workspace supporting team members, external vendors, or auto-labeling for large-scale datasets.
Data streaming
Reduce costs and memory requirements. Download only necessary data for specific tasks. Use familiar data loaders interface to minimize expensive GPU idle time.
Get the most out of your organization’s data with
Data Engine
Streamline your data processes, from handling unstructured data to model deployment, and enhance efficiency across your organization.
Centralized platform
Manage your ML projects from one place and build a central source of truth for your team. Bring order to the chaos in your datasets.
No DevOps required
Use an out-of-the-box solution for data management and have your team focus on the ML.
Improve model performance
Use active learning to improve the quality of your data and annotations to build better models.
Enhanced collaboration
Have the data, annotations, metadata, and subsets accessible to all team members without creating duplicates.
Move faster to production
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Save resources
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Reproduce results
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Iterate faster on your data
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Efficient and reliable workflows
Trusted by 22,000+ ML practitioners and teams
Don’t just take our word for it..
“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.”
Hwan Goh
| Head of Machine Learning | MACSO
“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.”
Isaac Faber
| Director of AI Development U.S. Army AI Integration Center
“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.”
Guy Rosin
| Applied Scientist | Mana.bio
“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.”
Francesco Curia
| Head of Data & AI | CY4GATE
