Merge pull request #234748 from pritamso/Broken-link-fix-alkohli

LinkFix: Broken link fixed

Author: prmerger-automator[bot]

articles/databox-online/azure-stack-edge-gpu-modify-fpga-modules-gpu.md

@@ -206,8 +206,7 @@ To set memory and CPU usage, use processor limits for modules in the `k8s-experi
 ```
 The memory and CPU specification are not necessary but generally good practice. If `requests` isn't specified, the values set in limits are used as the minimum required. 
 
-Using shared memory for modules also requires a different way. For example, you can use the Host IPC mode for shared memory access between Live Video Analytics and Inference solutions as described in [Deploy Live Video Analytics on Azure Stack Edge](../azure-video-analyzer/video-analyzer-docs/overview.md).
-
+Using shared memory for modules also requires a different way. For example, you can use the Host IPC mode for shared memory access between Live Video Analytics and Inference solutions as described in [Deploy Live Video Analytics on Azure Stack Edge](/previous-versions/azure/azure-video-analyzer/video-analyzer-docs/articles/azure-video-analyzer/video-analyzer-docs/overview).
 
 ## Web proxy 
 

articles/machine-learning/tutorial-pipeline-python-sdk.md

@@ -150,7 +150,7 @@ First, create a directory to store the file in.
 
 Now, create the file in the dependencies directory.
 
-[!Notebook-python[] (~/azureml-examples-main/tutorials/e2e-ds-experience/e2e-ml-workflow.ipynb?name=conda.yml)]
+[!Notebook-python[] (~/azureml-examples-main/tutorials/e2e-ds-experience/e2e-ml-workflow.ipynb?name=conda.yaml)]
 
 The specification contains some usual packages, that you'll use in your pipeline (numpy, pip), together with some Azure Machine Learning specific packages (azureml-defaults, azureml-mlflow).