Update concept-mlflow.md

Author: pritamso

articles/machine-learning/concept-mlflow.md

@@ -80,7 +80,7 @@ Learn more at [Guidelines for deploying MLflow models](how-to-deploy-mlflow-mode
 * [Deploy MLflow to Online Endpoints](https://github.com/Azure/azureml-examples/blob/main/sdk/python/using-mlflow/deploy/mlflow_sdk_online_endpoints.ipynb): Demonstrates how to deploy models in MLflow format to online endpoints using MLflow SDK.
 * [Deploy MLflow to Online Endpoints with safe rollout](https://github.com/Azure/azureml-examples/blob/main/sdk/python/using-mlflow/deploy/mlflow_sdk_online_endpoints_progresive.ipynb): Demonstrates how to deploy models in MLflow format to online endpoints using MLflow SDK with progressive rollout of models and the deployment of multiple model's versions in the same endpoint.
 * [Deploy MLflow to web services (V1)](https://github.com/Azure/azureml-examples/blob/main/sdk/python/using-mlflow/deploy/mlflow_sdk_web_service.ipynb): Demonstrates how to deploy models in MLflow format to web services (ACI/AKS v1) using MLflow SDK.
-* [Deploying models trained in Azure Databricks to Azure Machine Learning with MLflow](https://github.com/Azure/azureml-examples/blob/main/sdk/python/using-mlflow/no-code-deployment/track_with_databricks_deploy_aml.ipynb): Demonstrates how to train models in Azure Databricks and deploy them in Azure ML. It also includes how to handle cases where you also want to track the experiments with the MLflow instance in Azure Databricks.
+* [Deploying models trained in Azure Databricks to Azure Machine Learning with MLflow](https://github.com/Azure/azureml-examples/blob/main/sdk/python/using-mlflow/deploy/track_with_databricks_deploy_aml.ipynb): Demonstrates how to train models in Azure Databricks and deploy them in Azure ML. It also includes how to handle cases where you also want to track the experiments with the MLflow instance in Azure Databricks.
 
 ## Training MLflow projects (preview)