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docs/clearml_data/best_practices.md
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@@ -29,19 +29,19 @@ Like any ClearML tasks, datasets can be organized into [projects (and subproject
Additionally, when creating a dataset, tags can be applied to the dataset, which will make searching for the dataset easier.
Organizing your datasets into projects by use-case makes it easier to access the most recent dataset version for that use-case.
If only a project is specified when using [`Dataset.get`](../references/sdk/dataset.md#datasetget), the method returns the
If only a project is specified when using [`Dataset.get()`](../references/sdk/dataset.md#datasetget), the method returns the
most recent dataset in a project. The same is true with tags; if a tag is specified, the method will return the most recent dataset that is labeled with that tag.
In cases where you use a dataset in a task (e.g. consuming a dataset), you can easily track which dataset the task is
using by using `Dataset.get`'s `alias` parameter. Pass `alias=<dataset_alias_string>`, and the task using the dataset
using by using `Dataset.get()`'s `alias` parameter. Pass `alias=<dataset_alias_string>`, and the task using the dataset
will store the dataset's ID in the `dataset_alias_string` parameter under the task's **CONFIGURATION > HYPERPARAMETERS >
Datasets** section.
## Document your Datasets
Attach informative metrics or debug samples to the Dataset itself. Use the [`get_logger`](../references/sdk/dataset.md#get_logger)
method to access the dataset's logger object, then add any additional information to the dataset, using the methods
Attach informative metrics or debug samples to the Dataset itself. Use [`Dataset.get_logger()`](../references/sdk/dataset.md#get_logger)
to access the dataset's logger object, then add any additional information to the dataset, using the methods
available with a [logger](../references/sdk/logger.md) object.
You can add some dataset summaries (like [table reporting](../references/sdk/logger.md#report_table)) to create a preview