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allegroai 2020-12-22 23:45:44 +02:00
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@ -22,7 +22,7 @@ ClearML is a ML/DL development and production suite, it contains three main modu
- [Experiment Manager](#clearml-experiment-manager) - Automagical experiment tracking, environments and results
- [ML-Ops](https://github.com/allegroai/clearml-agent) - Automation, Pipelines & Orchestration solution for ML/DL jobs (K8s / Cloud / bare-metal)
- [Data-Management](https://github.com/allegroai/clearml/blob/master/docs/clearml-task.md) - Fully differentiable data management & version control solution on top of object-storage
- [Data-Management](https://github.com/allegroai/clearml/blob/master/docs/datasets.md) - Fully differentiable data management & version control solution on top of object-storage
(S3/GS/Azure/NAS)

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## Decoupling Data from Code - The Dataset Paradigm
<a href="https://app.community.clear.ml"><img src="https://github.com/allegroai/clearml/blob/master/docs/dataset_screenshots.gif?raw=true" width="80%"></a>
### The ultimate goal of `clearml-data` is to transform datasets into configuration parameters
Just like any other argument, the dataset argument should retrieve a full local copy of the
dataset to be used by the experiment.
@ -136,4 +138,3 @@ in the differential snapshot (location / size / hash), is available in the Artif
This allows you to quickly compare two dataset contents and visually see the difference.
- The dataset genealogy DAG and change-set summary table is visualized in Results / Plots
<a href="https://app.community.clear.ml"><img src="https://github.com/allegroai/clearml/blob/master/docs/dataset_screenshots.gif?raw=true" width="80%"></a>