Neptune in 3 minutes¶
Try Neptune on Colab with zero setup and see results in the UI¶
Get a quick feel of how monitoring and keeping track of experiments can look like.
What does Neptune do?¶
Neptune is a lightweight experiment management tool that helps you keep track of your machine learning experiments.
Most common Neptune use cases:
How does Neptune work (in 3 steps)?¶
Following snippets are just to give you the idea.
If you want to copy paste and run things quickly then go to Quick starts.
Connect it to your script
Start an experiment
Log things that you care about
neptune.log_metric('test_auc', 0.92) # metrics, losses neptune.log_image('charts', roc_curve_fig) # images, charts neptune.log_artifact('model.h5') # model binaries, predictions, files
Run your script normally
See everything in Neptune UI
Check it for yourself:
See our Quick starts
Example project: See how example project looks in Neptune
YouTube channel: Provides hands-on videos that showcase key Neptune features.
Neptune blog: Provides in-depth articles about best practices in machine learning experimentation (among other things)
neptune-client: Neptune client is an open source Python library that lets you integrate your Python scripts with Neptune.
neptune-contrib: Built on top of neptune-client, this is an open-source collection of advanced utilities that make work with Neptune easier.
Questions? Send an email to firstname.lastname@example.org by email or click the chat icon in the bottom right corner.