Neptune comes with 25+ integrations with Python libraries popular in machine learning, deep learning and reinforcement learning.
How integrations work?¶
Integrations are written using neptune-client and provide a convenient way to jump-start working with Neptune and a library that you are using. There is no need to integrate your code manually using neptune-client (it’s easy though).
Each integration, that is installation, scope and usage example are explained in detail in the documentation (see: PyTorch Lightning for example).
You can always use neptune-client to log data to experiments . If you need more control or explicit logging, you can always use it (all integrations use it anyway).
List of all integrations¶
Ray/Tune coming soon…
Hydra coming soon…
ACME coming soon…
Spinning up coming soon…
Stable baselines coming soon…
My library is not here. What now?¶
There are two common paths:
You can always use neptune-client , our open source Python library for logging all kinds of data and metadata to experiments.
Contact us directly via mail (email@example.com) or chat (that little thing in the lower right corner) to discuss what you need and how we can deliver it.