MLReef

Score9.1 out of 10

1 Reviews and Ratings

What is MLReef?

Read more details.

Categories & Use Cases

Media

Screenshot of ML Pipeline creation - from fully flexible git repositories to addressable, explorable and easy accessible drag-and-drop elements

Screenshot of A knowledgebase for your organization: ML Projects and AI Modules (scripts)

Screenshot of Full version control and transparent experiment tracking

Screenshot of Repositories to manage your scripts (SCM) and data (pipelines)

Screenshot of Manage your team, groups and projects with access rights and granular permissions

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Screenshot of ML Pipeline creation - from fully flexible git repositories to addressable, explorable and easy accessible drag-and-drop elements

Hans-Michael Hauser

Founder & CEO in Corporate at ML Insights AG (1-10 employees employees)

Use Cases and Deployment Scope

Distributed Machine Learning Operations is very important for delivering Machine Learning Projects to our customers.

Pros

Helps us to take on more client projects
Can be used by data analysts as well as casual users

Cons

Out of the box support for major cloud vendors

Most Important Features

Allowing distributed learning
Easy to learn

Return on Investment

We can handle 4 to 6 times more projects at the same time with our team
We stay engaged with our customers well beyond the project duration

Other Software Used

Jira Software, GitLab