Hyperdash
Hyperdash is a machine learning monitoring library capable of running alongside Tensorflow, Scikit-Learn, and other modeling libraries. It was developed with a focus on enabling fast knowledge gain.
Use Hyperdash if you’re looking for cloud-based model monitoring that:
Is fast and easy-to-use with scripts and Jupyter.
Tracks your hyperparameters across different model experiments.
Graphs performance metrics (loss, reward, etc.) in real-time.
Can be viewed remotely on the Web, iOS, and Android without self-hosting (e.g. Tensorboard).
Saves your experiment’s print output (standard out / error) as a local log file.
Notifies you when a long-running experiment has finished.
Hyperdash is compatible with: Python 2.7 - 3.6
1 maintainer
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Release files for hyperdash 0.15.3
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
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| hyperdash-0.15.3.tar.gz | 24.9 kB | Without provenance | Details for hyperdash-0.15.3.tar.gz |
Release files / hyperdash-0.15.3.tar.gz
| Download URL | hyperdash-0.15.3.tar.gz |
|---|---|
| Size | 24.9 kB |
| Tags | Source |
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Security for hyperdash 0.15.3
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