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).
Integrations are organized into the following categories:
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).
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.