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Author: nibaccam

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

@@ -186,13 +186,13 @@ Learn about the specific definitions of these metrics in [Understand automated m
 
 In every automated machine learning experiment, your data is [automatically scaled and normalized](concept-automated-ml.md#preprocess) to help *certain* algorithms that are sensitive to features that are on different scales.  However, you can also enable additional featurization, such as missing values imputation, encoding, and transforms. [Learn more about what featurization is included](how-to-create-portal-experiments.md#featurization).
 
-When configuring your experiments, you can enable the advanced setting `feauturization`. The following table shows the accepted settings for featurization in the [`AutoMLConfig` class](https://docs.microsoft.com/python/api/azureml-train-automl/azureml.train.automl.automlconfig?view=azure-ml-py).
+When configuring your experiments, you can enable the advanced setting `featurization`. The following table shows the accepted settings for featurization in the [`AutoMLConfig` class](https://docs.microsoft.com/python/api/azureml-train-automl/azureml.train.automl.automlconfig?view=azure-ml-py).
 
 |Featurization Configuration | Description |
 | ------------- | ------------- |
-|`"feauturization":` `'FeaturizationConfig'`| Indicates customized featurization step should be used. [Learn how to customize featurization](how-to-configure-auto-train.md#customize-feature-engineering).|
-|`"feauturization": 'off'`| Indicates featurization step should not be done automatically.|
-|`"feauturization": 'auto'`| Indicates that as part of preprocessing, [data guardrails and featurization steps](how-to-create-portal-experiments.md#advanced-featurization-options) are performed automatically.|
+|`"featurization":` `'FeaturizationConfig'`| Indicates customized featurization step should be used. [Learn how to customize featurization](how-to-configure-auto-train.md#customize-feature-engineering).|
+|`"featurization": 'off'`| Indicates featurization step should not be done automatically.|
+|`"featurization": 'auto'`| Indicates that as part of preprocessing, [data guardrails and featurization steps](how-to-create-portal-experiments.md#advanced-featurization-options) are performed automatically.|
 
 > [!NOTE]
 > Automated machine learning featurization steps (feature normalization, handling missing data,