MLReef - the first true MLOPs platform
MLReef is filling the gap for a true holistic MLOps platform - one, that covers all basic needs for state-of-the-art Machine Learning development.
The following links provide documentation for each MLOps stage:
|Features to create.
|Pipelines and experiments.
|Projects, users, groups and resources.
|Releasing code repositories.
MLReef consolidates your ML projects in one distributed version control system that´s easily managed and processed without disrupting your workflow.
|All create topics
|Creating and managing ML projects.
|Creating and managing models.
|Creating and managing dataOps.
|Creating and managing data visualizations.
|Understanding MLRee's core infrastructure.
MLreef is built from ground up to offer the highest degree of collaboration, within your team and throughout the entire MLReef community. The marketplace offers you instant access to ML projects, models and data operations.
The following documentation relates to the MLOps develop stage:
|All develop topics
|Data sourced pipelines for data preprocessing and visualization.
|Create experiments based on data with ML models.
|Metrics and model binary storage and download.
|Understanding and reproducing each value-added step.
Manage your Machine Learning pipeline like a pro! Manage users, groups and resources. The following documentation relates to the MLOps manage stage:
|All manage topics
|General overview of settings.
|Manage user access and roles in repositories.
Sharing is an essential part in MLReef and focused on sharing know-how and ML content. The elemental part is to share code repositories by releasing them to make them usable for yourself, your team or the entire community.
The following documentation relates to the MLOps share stage:
|All share topics
|Releasing code repositories
|Making code repositories available for use.
|Share your profile and discover other users.