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- Read-only API for fetching metadata tracked with the Neptune logging client.
neptune-exporter
PublicCLI tool to move Neptune experiments (version 2.x or 3.x) to disk as parquet + files, with an option to load them into MLflow or Weights & Biases.neptune-client-scale
Public- Neptune Fetcher is designed to separate data retrieval capabilities from the regular neptune package. This separation makes data fetching more efficient and improves performance.
- 📝 Examples of how to use Neptune for different use cases and with various MLOps tools
- 📘 The experiment tracker for foundation model training
- 📝 Examples of how to use Neptune for different use cases and with various MLOps tools
neptune-pytorch
PublicExperiment tracking for PyTorch. 🧩 Log, organize, visualize, and compare model metrics, hyperparameters, dataset versions, and more.neptune-detectron2
Publicneptune-aws
Publicneptune-mlflow
PublicNeptune - MLflow integration 🧩 Experiment tracking with advanced UI, collaborative features, and user access management.neptune-tensorboard
PublicNeptune - TensorBoard integration 🧩 Experiment tracking with advanced UI, collaborative features, and user access management.neptune-contrib
Public archiveThis library is a location of the LegacyLogger for PyTorch Lightning.neptune-deployment-tests
Publicneptune-optuna
Public🚀 Optuna visualization dashboard that lets you log and monitor hyperparameter sweep live.kedro-neptune
Publicneptune-tensorflow-keras
Public- Experiment tracking for scikit-learn. 🧩 Log, organize, visualize and compare model metrics, parameters, dataset versions, and more.
neptune-sacred
Publicneptune-prophet
Publicpyproject-flake8
Publicneptune-airflow
Public- 📚 Jupyter Notebooks extension for versioning, managing and sharing notebook checkpoints in your machine learning and data science projects.
load-generator
Publicneptune-r
Public📒 The MLOps stack component for experiment tracking (R interface)neptune-xgboost
PublicExperiment tracking for XGBoost. 🧩 Log, organize, visualize and compare machine learning model metrics, parameters, dataset versions, and more.