Update how-to-log-mlflow-models.md

Author: pritamso

articles/machine-learning/how-to-log-mlflow-models.md

@@ -54,7 +54,7 @@ accuracy = accuracy_score(y_test, y_pred)
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-> If you are using Machine Learning pipelines, like for instance [Scikit-Learn pipelines](https://scikit-learn.org/stable/modules/generated/sklearn.pipeline.Pipeline.html), use the `autolog` functionality of that flavor for logging models. Models are automatically logged when the `fit()` method is called on the pipeline object. The notebook [Training and tracking an XGBoost classifier with MLflow](https://github.com/Azure/azureml-examples/blob/main/sdk/python/using-mlflow/train-with-mlflow/xgboost_classification_mlflow.ipynb) demonstrates how to log a model with preprocessing using pipelines.
+> If you are using Machine Learning pipelines, like for instance [Scikit-Learn pipelines](https://scikit-learn.org/stable/modules/generated/sklearn.pipeline.Pipeline.html), use the `autolog` functionality of that flavor for logging models. Models are automatically logged when the `fit()` method is called on the pipeline object. The notebook [Training and tracking an XGBoost classifier with MLflow](https://github.com/Azure/azureml-examples/blob/main/sdk/python/using-mlflow/train-and-log/xgboost_classification_mlflow.ipynb) demonstrates how to log a model with preprocessing using pipelines.
 
 ## Logging models with a custom signature, environment or samples