What is Neptune?

Neptune is a data science collaboration hub. With Neptune, teams can work together efficiently and keep all aspects of their workflow in a single place. Whether it is source code, jupyter notebooks, model training curves or meeting notes, Neptune got you covered.


Neptune is lightweight

Neptune is built with the single design principle in mind: lightweightness. What does it mean in practice?

  • easy user onboarding: if you know how to use print() you will learn how to use it in no time.

  • 20-minute deployment: use SaaS, deploy on any cloud or on your hardware.

  • Neptune fits in any workflow, ranging from data exploration & analysis, decision science to machine learning and deep learning.

  • Neptune works with common technologies in data science domain: Python 2 and 3, Jupyter Notebooks, R.

  • Neptune integrates with other tools like MLflow and TensorBoard.

Neptune’s focus: track, organize and collaborate

We put focus on three aspects of the team work on data science projects: track, organize and collaborate.


Track all objects in the data science or machine learning project. It can be model training curves, visualizations, input data, calculated features and so on. Snippet below, presents example integration with Python code.

import neptune

with neptune.create_experiment():
    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)


Organize structure of your project:

  • code

  • notebooks

  • experiment results

  • model weights

  • meeting notes,

  • reports

Everything is in one place, accessible from the app or programatically!


Collaborate in the team:

  • share your experiments

  • compare results

  • comment and communicate your work.

  • interactive widgets focused on data science

Speak Your language in our data-science focused interactive wiki!


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