links

Author: nibaccam

articles/machine-learning/how-to-use-mlflow.md

@@ -18,7 +18,7 @@ ms.custom: devx-track-python, mlflow
 In this article, learn how to enable MLflow's tracking URI and logging API, collectively known as [MLflow Tracking](https://mlflow.org/docs/latest/quickstart.html#using-the-tracking-api), to connect Azure Machine Learning as the backend of your MLflow experiments. 
 
 > [!TIP]
-> For a more streamlined experience, see how to [Track experiments with the MLflow SDK or the Azure Machine Learning CLI (v2) (preview)](how-to-use-mlflow-cli.md)
+> For a more streamlined experience, see how to [Track experiments with the MLflow SDK or the Azure Machine Learning CLI (v2) (preview)](how-to-use-mlflow-cli-runs.md)
 
 Supported capabilities include: 
 

articles/machine-learning/toc.yml

@@ -473,7 +473,7 @@
                 href: how-to-track-monitor-analyze-runs.md
               - name: Track experiments with MLflow and CLI (v2)
                 displayName: log, monitor, metrics, model registry, register
-                href: how-to-use-mlflow-cli.md
+                href: how-to-use-mlflow-cli-runs.md
               - name: Track Azure Databricks runs with MLflow
                 displayName: log, monitor, deploy, metrics, databricks
                 href: how-to-use-mlflow-azure-databricks.md