TensorBoard is a great first tool to track experiments
Moved on to more complex models? Not so much
You feel comfortable with TensorBoard because youāve used it since your student days.
And youāre still using it because itās open source. But the longer you work on larger,
more complicated experiments, the more uncomfortable TensorBoardās limitations become.
Itās time you tried a more sophisticated solution.
workspace set-up
visualization
user support
Choose Neptune when entry-level experiment tracking is tying you down
Maintenance
All your metadata, always available
Restart your server. Wait. Download your logs to a machine with a graphical interface. Plot them. Every. Single. Time. Just to look at your metrics?! Youāre sure there must be a better way. With Neptune, there isā¦
Neptuneās hosted solution allows you to log all your data into a central metadata store. All your experiments are available instantly, online, and from any machine. You no longer need DevOps just to display your logs.
Team
Crafted for collaboration
The CSVs and screenshots you send to share your work can (and do!) easily get lost. The more complex your work, the more frustrated you get relying on clumsy workarounds.Ā
Neptuneās built-in collaborative features make teamwork effortless. Centralized data means all your team members can see exactly what everyone else is doing. And sharing your work is simple, with comparison tables and persistent links to Neptuneās web app.
Scalability
Will scale. Wonāt fail.
Neptune wonāt explode ā or even slow down ā when you reach 100 runs. You can run hundreds of experiments simultaneously with zero effect on performance.Ā
Even when rendering complex charts to view your data ā like Matpolib figures or Bokeh plots ā Neptune will never let you down.
Interface
Compare experiments without the clutter
Managing experiments without proper structures for your projects can be a messy business. Not with Neptune.
With our intuitive user interface, you can easily:
- organize your experimentsā metadata in a customizable folder-like structure,
- visualize your runsā parameters and metrics. And log interactive visualizations to Neptune,
- compare your experiments with 4 types of comparison views (Charts, Parallel Coordinates, Side-by-side, Artifacts).
Take a deep dive into
what makes Neptune different
Neptune
TensorBoard
Commercial Requirements
Standalone component. ML metadata store that focuses on experiment tracking and model registry
Open source tool which is a part of the TensorFlow ecosystem
TensorBoard is hosted locally. No
TensorBoard.dev is available on a managed server as a free service
Managed cloud service
TensorBoard is open-source, while TensorBoard.dev is available as a free managed cloud service
General Capabilities
No special requirements other than having the neptune-client installed and access to the internet if using managed hosting. Check here for infrastructure requirements for on-prem deployment
Basic logging can be done by having just TensorBoard installed. However, most advanced logging also requires TensorFlow to be installed
Minimal. Just a few lines of code needed for tracking. Read more
Minimal if already using the TensorFlow framework, else significant
Yes, through the neptune-client library
TensorBoard is available both as a client library and CLI. TensorBoard .dev is available only as a CLI
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Experiment Tracking
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Query language
Regex with limited query language on the TensorBoard.dev experiments homepage
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Limited
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Model Registry
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Limited
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Integrations and Support
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