Neptune

Logging and visualizing experiments with neptune.ai

The Neptune Experiment Tracker is an Experiment Tracker flavor provided with the Neptune-ZenML integration that uses neptune.ai to log and visualize information from your pipeline steps (e.g. models, parameters, metrics).

When would you want to use it?

Neptune is a popular tool that you would normally use in the iterative ML experimentation phase to track and visualize experiment results or as a model registry for your production-ready models. Neptune can also track and visualize the results produced by your automated pipeline runs, as you make the transition towards a more production-oriented workflow.

You should use the Neptune Experiment Tracker:

if you have already been using neptune.ai to track experiment results for your project and would like to continue doing so as you are incorporating MLOps workflows and best practices in your project through ZenML.

if you are looking for a more visually interactive way of navigating the results produced from your ZenML pipeline runs (e.g. models, metrics, datasets)

if you would like to connect ZenML to neptune.ai to share the artifacts and metrics logged by your pipelines with your team, organization, or external stakeholders

You should consider one of the other Experiment Tracker flavors if you have never worked with neptune.ai before and would rather use another experiment tracking tool that you are more familiar with.

How do you deploy it?

The Neptune Experiment Tracker flavor is provided by the Neptune-ZenML integration. You need to install it on your local machine to be able to register the Neptune Experiment Tracker and add it to your stack:

zenml integration install neptune -y

The Neptune Experiment Tracker needs to be configured with the credentials required to connect to Neptune using an API token.

Authentication Methods

You need to configure the following credentials for authentication to Neptune: