What is Neptune?

Neptune is a collaboration platform for data science / machine learning teams that focuses on three areas:

  • Track: all metrics and outputs in your data science or machine learning project. It can be model training curves, visualizations, input data, calculated features and so on.

  • Organize: automatically transform tracked data into a knowledge repository.

  • Collaborate: share, compare and discuss your work across data science project.

What is Neptune client?

Neptune client is open source Python library that allows Users to integrate their Python scripts with Neptune.

Note

Make sure to register to Neptune, to use it.

Installation

pip install neptune-client

Once installed, import neptune in your code to use it.

Example

import neptune

neptune.init('shared/onboarding')
with neptune.create_experiment(name='simple_example'):
    neptune.append_tag('minimal-example')
    n = 117
    for i in range(1, n):
        neptune.send_metric('iteration', i)
        neptune.send_metric('loss', 1/i**0.5)
    neptune.set_property('n_iterations', n)

Example above creates Neptune experiment in the project: shared/onboarding and logs iteration and loss metrics to Neptune in real time. It also presents common use case for Neptune client, that is tracking progress of machine learning experiments.

Miscellaneous

Bugs, feature requests and questions

If you find yourself in any trouble drop an issue on GitHub issues, fire a feature request on GitHub feature request or ask us on the Neptune community forum or Neptune community spectrum.