Update how-to-track-experiments-mlflow.md

Author: pritamso

articles/machine-learning/how-to-track-experiments-mlflow.md

@@ -260,8 +260,8 @@ To compare and evaluate the quality of your jobs and models in AzureML Studio, u
 
 The [MLflow with Azure ML notebooks](https://github.com/Azure/azureml-examples/tree/main/sdk/python/using-mlflow) demonstrate and expand upon concepts presented in this article.
 
-  * [Training and tracking a 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 track experiments using MLflow, log models and combine multiple flavors into pipelines.
-  * [Manage experiments and runs with MLflow](https://github.com/Azure/azureml-examples/blob/main/sdk/python/using-mlflow/run-history/run_history.ipynb): Demonstrates how to query experiments, runs, metrics, parameters and artifacts from Azure ML using MLflow.
+  * [Training and tracking a 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 track experiments using MLflow, log models and combine multiple flavors into pipelines.
+  * [Manage experiments and runs with MLflow](https://github.com/Azure/azureml-examples/blob/main/sdk/python/using-mlflow/runs-management/run_history.ipynb): Demonstrates how to query experiments, runs, metrics, parameters and artifacts from Azure ML using MLflow.
 
 
 ## Support matrix for querying runs and experiments