DagsHub | Team | per user| month

DagsHub is a collaborative platform designed for machine learning (ML) and data science teams to manage, version, and track their projects seamlessly. It provides a GitHub-like experience but is tailored specifically for ML workflows, integrating key tools such as DVC (Data Version Control), MLflow, and Jupyter Notebooks. DagsHub enables teams to work efficiently on datasets, models, and code while ensuring full reproducibility and collaboration.

One of DagsHub’s core strengths is its ability to handle data and model versioning, making it easy to track changes in datasets and models just like software engineers track code changes with Git. It integrates remote storage solutions, allowing teams to store and manage large datasets efficiently without compromising accessibility or speed.

DagsHub also simplifies experiment tracking with MLflow, enabling users to monitor model training performance, compare results, and optimize hyperparameters. Additionally, its interactive visualization tools help data scientists gain deeper insights into model performance, dataset quality, and workflow efficiency. The platform also supports real-time collaboration, allowing team members to annotate data, review changes, and discuss improvements in a centralized environment.

Designed for both small teams and large enterprises, DagsHub accelerates ML development by providing a structured, version-controlled, and scalable workflow for machine learning projects. Whether you’re working on research, production models, or data pipelines, DagsHub ensures seamless collaboration and reproducibility.