Merge pull request #206391 from sdgilley/sdg-v2

SDK v1 tutorial

Author: v-ccolin

articles/machine-learning/tutorial-1st-experiment-bring-data.md

@@ -1,5 +1,5 @@
 ---
-title: "Tutorial: Upload data and train a model"
+title: "Tutorial: Upload data and train a model (SDK v2)"
 titleSuffix: Azure Machine Learning
 description: How to upload and use your own data in a remote training job. This is part 3 of a three-part getting-started series.
 services: machine-learning
@@ -10,13 +10,17 @@ author: aminsaied
 ms.author: amsaied
 ms.reviewer: sgilley
 ms.date: 07/10/2022
-ms.custom: tracking-python, contperf-fy21q3, FY21Q4-aml-seo-hack, contperf-fy21q4, sdkv1, event-tier1-build-2022
+ms.custom: tracking-python, contperf-fy21q3, FY21Q4-aml-seo-hack, contperf-fy21q4, sdkv2
 ---
 
 # Tutorial: Upload data and train a model (part 3 of 3)
 
 [!INCLUDE [sdk v2](../../includes/machine-learning-sdk-v2.md)]
 
+> [!div class="op_single_selector" title1="Select the version of Azure Machine Learning SDK you are using:"]
+> * [v1](v1/tutorial-1st-experiment-bring-data.md)
+> * [v2 (preview)](tutorial-1st-experiment-bring-data.md)
+
 This tutorial shows you how to upload and use your own data to train machine learning models in Azure Machine Learning. This tutorial is *part 3 of a three-part tutorial series*.
 
 In [Part 2: Train a model](tutorial-1st-experiment-sdk-train.md), you trained a model in the cloud, using sample data from `PyTorch`. You also downloaded that data through the `torchvision.datasets.CIFAR10` method in the PyTorch API. In this tutorial, you'll use the downloaded data to learn the workflow for working with your own data in Azure Machine Learning.

articles/machine-learning/tutorial-1st-experiment-hello-world.md

@@ -1,5 +1,5 @@
 ---
-title: "Tutorial: Get started with a Python script"
+title: "Tutorial: Get started with a Python script (SDK v2)"
 titleSuffix: Azure Machine Learning
 description: Get started with your first Python script in Azure Machine Learning. This is part 1 of a three-part getting-started series.
 services: machine-learning
@@ -10,13 +10,17 @@ author: aminsaied
 ms.author: amsaied
 ms.reviewer: sgilley
 ms.date: 07/10/2022
-ms.custom: devx-track-python, FY21Q4-aml-seo-hack, contperf-fy21q4, sdkv1, event-tier1-build-2022
+ms.custom: devx-track-python, FY21Q4-aml-seo-hack, contperf-fy21q4, sdkv2
 ---
 
 # Tutorial: Get started with a Python script in Azure Machine Learning (part 1 of 3)
 
 [!INCLUDE [sdk v2](../../includes/machine-learning-sdk-v2.md)]
 
+> [!div class="op_single_selector" title1="Select the version of Azure Machine Learning SDK you are using:"]
+> * [v1](v1/tutorial-1st-experiment-hello-world.md)
+> * [v2 (preview)](tutorial-1st-experiment-hello-world.md)
+
 In this tutorial, you run your first Python script in the cloud with Azure Machine Learning. This tutorial is *part 1 of a three-part tutorial series*.
 
 This tutorial avoids the complexity of training a machine learning model. You will run a "Hello World" Python script in the cloud. You will learn how a control script is used to configure and create a run in Azure Machine Learning.
@@ -144,7 +148,7 @@ Here's a description of how the control script works:
       `ml_client = MLClient(DefaultAzureCredential(), subscription_id, resource_group, workspace)`
    :::column-end:::
    :::column span="2":::
-      [MLClient](/python/api/azure-ai-ml/azure.ai.ml.mlclient) manages your Azure Machine Learning workspace and it's assets and resources.
+      [MLClient](/python/api/azure-ai-ml/azure.ai.ml.mlclient) manages your Azure Machine Learning workspace and its assets and resources.
    :::column-end:::
 :::row-end:::
 :::row:::

articles/machine-learning/tutorial-1st-experiment-sdk-train.md

@@ -1,5 +1,5 @@
 ---
-title: "Tutorial: Train a first Python machine learning model "
+title: "Tutorial: Train a first Python machine learning model (SDK v2)"
 titleSuffix: Azure Machine Learning
 description: How to train a machine learning model in Azure Machine Learning. This is part 2 of a three-part getting-started series.
 services: machine-learning
@@ -10,13 +10,17 @@ author: aminsaied
 ms.author: amsaied
 ms.reviewer: sgilley
 ms.date: 07/10/2022
-ms.custom: devx-track-python, contperf-fy21q3, FY21Q4-aml-seo-hack, contperf-fy21q, sdkv1, event-tier1-build-2022
+ms.custom: devx-track-python, contperf-fy21q3, FY21Q4-aml-seo-hack, contperf-fy21q, sdkv2
 ---
 
 # Tutorial: Train your first machine learning model (part 2 of 3)
 
 [!INCLUDE [sdk v2](../../includes/machine-learning-sdk-v2.md)]
 
+> [!div class="op_single_selector" title1="Select the version of Azure Machine Learning SDK you are using:"]
+> * [v1](v1/tutorial-1st-experiment-sdk-train.md)
+> * [v2 (preview)](tutorial-1st-experiment-sdk-train.md)
+
 This tutorial shows you how to train a machine learning model in Azure Machine Learning. This tutorial is _part 2 of a three-part tutorial series_.
 
 In [Part 1: Run "Hello world!"](tutorial-1st-experiment-hello-world.md) of the series, you learned how to use a control script to run a job in the cloud.
@@ -251,7 +255,7 @@ if __name__ == "__main__":
 
 ### View the output
 
-1. In the page that opens, you'll see the job status. The first time you run this script, Azure Machine Learning will build a new Docker image from your PyTorch environment. The whole job might around 10 minutes to complete. This image will be reused in future jobs to make them job much quicker.
+1. In the page that opens, you'll see the job status. The first time you run this script, Azure Machine Learning will build a new Docker image from your PyTorch environment. The whole job might take around 10 minutes to complete. This image will be reused in future jobs to make them job much quicker.
 1. You can see view Docker build logs in the Azure Machine Learning studio. Select the **Outputs + logs** tab, and then select **20_image_build_log.txt**.
 1. When the status of the job is **Completed**, select **Output + logs**.
 1. Select **std_log.txt** to view the output of your job.

articles/machine-learning/v1/toc.yml

@@ -45,6 +45,15 @@
 - name: Tutorials
   expanded: true
   items:
+    - name: Python get started (Day 1)
+      expanded: true
+      items: 
+        - name: 1. Run a Python script
+          href: tutorial-1st-experiment-hello-world.md
+        - name: 2. Train your model
+          href: tutorial-1st-experiment-sdk-train.md
+        - name: 3. Use your own data
+          href: tutorial-1st-experiment-bring-data.md
     - name: "Build a training pipeline (Python)"
       href: "tutorial-pipeline-python-sdk.md"
 - name: How-to guides