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

Author: santiagxf

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

@@ -15,7 +15,7 @@ ms.custom: how-to, devx-track-python, ignite-2022
 
 # Query & compare experiments and runs with MLflow
 
-Experiments and runs in Azure Machine Learning can be queried using MLflow. This removes the need of any Azure Machine Learning specific SDKs to manage anything that happens inside of a training job, allowing dependencies removal and creating a more seamless transition between local runs and cloud. 
+Experiments and runs tracking information in Azure Machine Learning can be queried using MLflow. You don't need to install any specific SDK to manage what happens inside of a training job, creating a more seamless transition between local runs and the cloud by removing cloud-specific dependencies. 
 
 > [!NOTE]
 > The Azure Machine Learning Python SDK v2 does not provide native logging or tracking capabilities. This applies not just for logging but also for querying the metrics logged. Instead, we recommend to use MLflow to manage experiments and runs. This article explains how to use MLflow to manage experiments and runs in Azure ML.