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Change headings to title caps (#62)
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@@ -28,7 +28,7 @@ Once we have a Task in ClearML, we can clone and edit its definition in the UI.
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- Create data monitoring & scheduling and launch inference jobs to test performance on any new coming dataset.
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- Once there are two or more experiments that run after another, group them together into a [pipeline](../../fundamentals/pipelines.md)
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## Manage your data
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## Manage Your Data
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Use [ClearML Data](../../clearml_data.md) to version your data, then link it to running experiments for easy reproduction.
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Make datasets machine agnostic (i.e. store original dataset in a shared storage location, e.g. shared-folder/S3/Gs/Azure)
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ClearML Data supports efficient Dataset storage and caching, differentiable & compressed
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@@ -123,7 +123,7 @@ from clearml import Task
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executed_task = Task.get_task(task_id='aabbcc')
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# get a summary of the min/max/last value of all reported scalars
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min_max_vlues = executed_task.get_last_scalar_metrics()
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# get detialed graphs of all scalars
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# get detailed graphs of all scalars
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full_scalars = executed_task.get_reported_scalars()
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```
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