Examples for using Neptune to log and retrieve your ML metadata.
You can run every example with zero setup as an "ANONYMOUS" Neptune user (no registration needed).
Note: This readme is best viewed in the GitHub Light theme.
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Neptune |
GitHub |
Colab |
Hello World |
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Docs |
Neptune |
GitHub |
Colab |
Organize ML experiments |
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Log binary classification metrics |
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Log fairness metrics |
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Docs |
Neptune |
GitHub |
Colab |
Log model building metadata |
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Docs |
Neptune |
GitHub |
Colab |
Monitor model training runs live |
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Docs |
Neptune |
GitHub |
Colab |
Do basic data versioning |
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Log image directory snapshot |
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Docs |
Neptune |
GitHub |
Colab |
Resume run |
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Pass Run object between files |
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Use Neptune in distributed computing |
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Use Neptune in parallel computing |
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Use Neptune in Pipelines |
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Log to multiple runs in one script |
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Docs |
Neptune |
GitHub |
Colab |
Do Groupby on runs |
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Do sorting |
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Integrations and Supported Tools
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Docs |
Neptune |
GitHub |
Colab |
Python |
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R |
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Docs |
Neptune |
GitHub |
Colab |
Catalyst |
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fastai |
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lightGBM |
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PyTorch |
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PyTorch Ignite |
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PyTorch Lightning |
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Scikit Learn |
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skorch |
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TensorFlow / Keras |
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XGBoost |
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Hyperparameter Optimization
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Docs |
Neptune |
GitHub |
Colab |
Keras Tuner |
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Optuna |
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Scikit Optimize |
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Model Visualization and Debugging
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Docs |
Neptune |
GitHub |
Colab |
Altair |
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Bokeh |
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Dalex |
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HiPlot |
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HTML |
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Matplotlib |
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Pandas |
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Plotly |
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Docs |
Neptune |
GitHub |
Colab |
MLflow |
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Sacred |
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TensorBoard |
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Docs |
Neptune |
GitHub |
Colab |
Any IDE |
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Amazon SageMaker notebooks |
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Deepnote |
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Google Colab |
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Jupyter Notebook and Jupyter Lab |
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Docs |
Neptune |
GitHub |
Colab |
AWS S3 |
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Data Version Control (DVC) |
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Local filesystem |
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Continuous Integration and Delivery (CI/CD)
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Docs |
Neptune |
GitHub |
Colab |
GitHub Actions |
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