Merge pull request #2886 from MicrosoftDocs/repo_sync_working_branch

Confirm merge from repo_sync_working_branch to main to sync with https://github.com/MicrosoftDocs/azure-ai-docs (branch main)

Author: Taojunshen

articles/machine-learning/how-to-deploy-with-triton.md

@@ -44,7 +44,7 @@ In this article, you will learn how to deploy a model using no-code deployment f
 * A working Python 3.8 (or higher) environment. 
 
 * You must have additional Python packages installed for scoring and may install them with the code below. They include:
-    * Numpy - An array and numerical computing library 
+    * NumPy - An array and numerical computing library 
     * [Triton Inference Server Client](https://github.com/triton-inference-server/client) - Facilitates requests to the Triton Inference Server
     * Pillow - A library for image operations
     * Gevent - A networking library used when connecting to the Triton Server
@@ -76,7 +76,7 @@ The information in this document is based on using a model stored in ONNX format
 * A working Python 3.8 (or higher) environment.
 
 * You must have additional Python packages installed for scoring and may install them with the code below. They include:
-    * Numpy - An array and numerical computing library 
+    * NumPy - An array and numerical computing library 
     * [Triton Inference Server Client](https://github.com/triton-inference-server/client) - Facilitates requests to the Triton Inference Server
     * Pillow - A library for image operations
     * Gevent - A networking library used when connecting to the Triton Server

articles/machine-learning/v1/concept-automated-ml.md

@@ -178,7 +178,7 @@ Using **Azure Machine Learning**, you can design and run your automated ML train
    * For limited or no code experience, try the Azure Machine Learning studio web experience at [https://ml.azure.com](https://ml.azure.com/)  
    * For Python developers, check out the [Azure Machine Learning Python SDK (v1)](../how-to-configure-auto-train.md) 
 
-1. **Specify the source and format of the labeled training data**: Numpy arrays or Pandas dataframe
+1. **Specify the source and format of the labeled training data**: NumPy arrays or Pandas dataframe
 
 1. **Configure the compute target for model training**, such as your [local computer, Azure Machine Learning Computes, remote VMs, or Azure Databricks with SDK v1](how-to-set-up-training-targets.md).
 

articles/machine-learning/v1/how-to-troubleshoot-auto-ml.md

@@ -113,7 +113,7 @@ As of version 1.5.0 of the SDK, automated machine learning does not install Tens
   run_config.environment.python.conda_dependencies = CondaDependencies.create(conda_packages=['tensorflow==1.12.0'])
 ```
 
-## Numpy failures
+## NumPy failures
 
 * **`import numpy` fails in Windows**: Some Windows environments see an error loading numpy with the latest Python version 3.6.8. If you see this issue, try with Python version 3.6.7.