ClearML Releases New Reports Feature to Share Real-Time Results of Machine Learning Projects and Ignite ML Collaboration Across the Enterprise

ClearML, the leading open source, end-to-end MLOps platform,  announced it has released a new Reports feature that is now generally available. This new feature makes it easy to create and share real-time reports within ClearML as well as connect to third-party editors such as Confluence, Monday, Notion, Colab (Jupyter), and others using embed code. A report can contain charts that auto-update continuously throughout an experiment lifecycle.

ClearML users can now easily create, collaborate on, and share reports, as well as graphs and charts, in order to summarize and explain experiments and how model versions improve, analyze results, show experiment comparisons, discuss bugs, demonstrate progress towards milestones, and publish their work.

“Reporting and showcasing your findings to colleagues, managers, or even your future self is a core component of any modern collaborative workflow,” said Moses Guttmann, Co-founder and CEO of ClearML. “Having one central place where you can seamlessly report, analyze, plan, and collaborate on your work in real time makes it that much easier. ClearML-Reports connects seamlessly with existing ClearML functionality and is based on markdown, so it’s very easy to export or connect to an external reporting tool.”

Recommended AI News: Fastly Acquires Fanout to Unlock Real-Time App Development at the Edge

Features and Benefits of ClearML Reports

The new ClearML Reports feature was designed with a multitude of functionality in mind, including:

• Creation: It’s now easy to write reports using markdown language, and there is a handy markdown cheatsheet to get started. Reports can be filtered by tags or archived like datasets or experiments.
• Visualization: Users can embed scalars, plots, or debug samples from the ClearML experiment manager right into the markdown editor with preview updates. They can even embed descriptive statistics of their datasets or comparisons graphs from multiple experiments — what’s important is that these are not HTML exports, but are still connected to the back-end such that when new data comes in, it will be visible after a report refresh.
• Team Collaboration: Teammates with ClearML logins can edit reports that are not published as read-only. Reports are also searchable based on their descriptions.
• Sharing of Reports: Users can share on-platform with others who have a ClearML login and can export to PDF for a time-bound report to share with anyone else. Publishing the report will make it read-only, so it can be used as a single source of truth among colleagues. Users can easily export your reports out of ClearML as markdown or PDF.
• External Tooling Integration: Many users and their teams each have their own workflows with their own toolchains. By not limiting the reporting functionality to only ClearML reports, users can easily integrate ClearML elements into their favorite third-party reporting tools, like Notion, Confluence, Monday, and others.

Recommended AI News: OmniML Secures $10 Million to Accelerate AI Computing on Edge Devices

“Reporting our findings on the weekly standups was quite manual,” said Omri Bar, AI Research Team Leader at Theator, the creator of Surgical Intelligence. “I’d have to jump around between experiments, moving from one plot to another, narrating what was interesting about the graph in question. That’s not very easy for my colleagues to follow along with. Now I can prepare a neat report ahead of time, with all the interesting parts embedded inside, important notes right next to them, cleanly organized by topic. It has made our communication much smoother.”

Recommended AI News: CommScope Propels Data Centers into the Future

[To share your insights with us, please write to sghosh@martechseries.com]