Improved assets tracking
Tracking assets and lineage information is an important aspect of machine learning reproducibility. In previous versions, users were often confused about the behavior of assets and artifacts tracking.
Polyaxon features two interfaces for tracking artifacts:
- Versioned assets tracking: useful when the user needs to save the same asset but several times in the same run.
- Reference tracking: gives users more control over where the asset must be saved.
We improved the interface and now have a documentation guide that explains the behavior and some use cases.
New ML/DL Callbacks
Callbacks and loggers allow an automated process for tracking params, metrics, charts, and assets. In v1.7, Polyaxon provides, several new callbacks for major deep learning and machine learning libraries and frameworks:
As well as several visualization libraries.
Better Documentation with Examples
We improved several aspects about the documentations:
New excutable components for several tracking integrations, you can copy/paste the components to the dashboard and run them to see how they work:
New quick-start guide for driving the complete cycle in a programmatic way using Python.
New quick-start guide for using presets to increase awareness about the feature and to improve iterations.
The examples repo was also updated with several corrections and new samples.
Learn More about Polyaxon
This blog post just goes over a couple of features that we shipped since our last product update, there are several other features and fixes that are worth checking. To learn more about all the features, fixes, and enhancements, please visit the release notes.
Polyaxon continues to grow quickly and keeps improving and providing the simplest machine learning abstraction. We hope that these updates will improve your workflows and increase your productivity, and again, thank you for your continued feedback and support.
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