MLflow

Neptune-mlflow is an open source project curated by Neptune team, that integrates MLflow with Neptune to let you get the best of both worlds. Enjoy tracking and reproducibility of MLflow with organization and collaboration of Neptune.

With neptune-mlflow you can have your mlflow experiment runs hosted in Neptune.

Resources

Quick-start

Installation

pip install neptune-mlflow

Sync your MLruns with Neptune

Navigate to your MLflow project in your directory and run:

neptune mlflow --project USER_NAME/PROJECT_NAME

Alternatively you can point to MLflow project directory:

neptune mlflow /PATH/TO/MLflow_PROJECT --project USER_NAME/PROJECT_NAME

Note

That’s it! You can now browse and collaborate on your MLflow runs in Neptune.

What next?

  1. Go to project documentation to learn more.

  2. Check our blog, where Neptune team publishes posts about variety of data science-related topics.

TensorBoard

Neptune-tensorboard is an open source project curated by Neptune team, that integrates TensorBoard with Neptune to let you get the best of both worlds.

With neptune-tensorboard you can have your TensorBoard visualizations hosted in Neptune.

Resources

Quick-start

Installation

pip install neptune-tensorboard

Sync TensorBoard logdir with Neptune

Point Neptune to your TensorBoard logs directory:

neptune tensorboard /PATH/TO/TensorBoard_logdir --project USER_NAME/PROJECT_NAME

Note

That’s it! You can now browse and collaborate on your TensorBoard runs in Neptune.

What next?

  1. Go to project documentation to learn more.

  2. Check our blog, where Neptune team publishes posts about variety of data science-related topics.

Neptune Contrib

Neptune-contrib is an open source project curated by Neptune team. It is collection of framework integrations, functions and other productivity helpers that makes your work with Neptune faster and more efficient.

Resources

Example tools:

Quick-start

Installation

pip install neptune-contrib

What next?

  1. It is highly recommended to skim through neptune-contrib docs. It contains number of examples and tutorials that show you how to use it.

  2. Check our blog, where Neptune team publishes posts about variety of data science-related topics.