Merge pull request #101541 from nibaccam/patch-3

Minor updates

Author: PRMerger12

articles/machine-learning/how-to-create-register-datasets.md

@@ -72,7 +72,7 @@ To create datasets from an [Azure datastore](how-to-access-data.md) by using the
 
 #### Create a TabularDataset
 
-You can create TabularDatasets through the SDK or by using Azure Machine Learning Studio. You can specify a time stamp from a column in the data or from the path pattern that the data is stored in to enable a time series trait. This specification allows for easy and efficient filtering by time.
+You can create TabularDatasets through the SDK or by using Azure Machine Learning studio. 
 
 Use the [`from_delimited_files()`](https://docs.microsoft.com/python/api/azureml-core/azureml.data.dataset_factory.tabulardatasetfactory?view=azure-ml-py#from-delimited-files-path--validate-true--include-path-false--infer-column-types-true--set-column-types-none--separator------header-true--partition-format-none-) method on the `TabularDatasetFactory` class to read files in .csv or .tsv format, and to create an unregistered TabularDataset. If you're reading from multiple files, results will be aggregated into one tabular representation.
 
@@ -184,7 +184,7 @@ titanic_ds = titanic_ds.register(workspace=workspace,
 ```
 
 > [!Note]
-> Datasets created through Azure Machine Learning Studio are automatically registered to the workspace.
+> Datasets created through Azure Machine Learning studio are automatically registered to the workspace.
 
 ## Create datasets with Azure Open Datasets
 
@@ -243,7 +243,6 @@ titanic_ds = titanic_ds.register(workspace = workspace,
                                  create_new_version = True)
 ```
 
-
 ## Access datasets in your script
 
 Registered datasets are accessible both locally and remotely on compute clusters like the Azure Machine Learning compute. To access your registered dataset across experiments, use the following code to access your workspace and registered dataset by name. By default, the [`get_by_name()`](https://docs.microsoft.com/python/api/azureml-core/azureml.core.dataset.dataset?view=azure-ml-py#get-by-name-workspace--name--version--latest--) method on the `Dataset` class returns the latest version of the dataset that's registered with the workspace.