Merge pull request #92777 from j-martens/patch-698

Update how-to-configure-auto-train.md

Author: PRMerger6

articles/machine-learning/service/how-to-configure-auto-train.md

@@ -66,28 +66,24 @@ automl_config = AutoMLConfig(task = "classification")
 
 ## Data source and format
 
-Automated machine learning supports data that resides on your local desktop or in the cloud such as Azure Blob Storage. The data can be read into a Pandas DataFrame or an Azure Machine Learning dataset. The following code examples demonstrate how to store the data in these formats. [Learn more about datatsets](https://github.com/MicrosoftDocs/azure-docs-pr/pull/how-to-create-register-datasets.md).
+Automated machine learning supports data that resides on your local desktop or in the cloud such as Azure Blob Storage. The data can be read into a **Pandas DataFrame** or an **Azure Machine Learning TabularDataset**.  [Learn more about datatsets](https://github.com/MicrosoftDocs/azure-docs-pr/pull/how-to-create-register-datasets.md).
 
-* TabularDataset
-* Pandas dataframe
-
->[!Important]
-> Requirements for training data:
->* Data must be in tabular form.
->* The value you want to predict (target column) must be present in the data.
+Requirements for training data:
+- Data must be in tabular form.
+- The value to predict, target column, must be in the data.
 
-Examples:
+The following code examples demonstrate how to store the data in these formats.
 
 * TabularDataset
-```python
-    from azureml.core.dataset import Dataset
-
-    tabular_dataset = Dataset.Tabular.from_delimited_files("https://automldemods.blob.core.windows.net/datasets/PlayaEvents2016,_1.6MB,_3.4k-rows.cleaned.2.tsv")
-    train_dataset, test_dataset = tabular_dataset.random_split(percentage = 0.1, seed = 42)
-    label = "Label"
-```
+  ```python
+  from azureml.core.dataset import Dataset
+  
+  tabular_dataset = Dataset.Tabular.from_delimited_files("https://automldemods.blob.core.windows.net/datasets/PlayaEvents2016,_1.6MB,_3.4k-rows.cleaned.2.tsv")
+  train_dataset, test_dataset = tabular_dataset.random_split(percentage = 0.1, seed = 42)
+  label = "Label"
+  ```
 
-*	Pandas dataframe
+* Pandas dataframe
 
     ```python
     import pandas as pd