1. An Azure subscription. If you don't have an Azure subscription, create a free account before you begin.

1. Install the SDK v2

pip install azure-ai-ml

git clone https://github.com/Azure/azureml-examples
cd azureml-examples/tutorials

Test Status is for branch - main

Title	Notebook	Description	Status
azureml-getting-started	azureml-getting-started-studio	A quickstart tutorial to train and deploy an image classification model on Azure Machine Learning studio
azureml-in-a-day	azureml-in-a-day	Learn how a data scientist uses Azure Machine Learning (Azure ML) to train a model, then use the model for prediction. This tutorial will help you become familiar with the core concepts of Azure ML and their most common usage.
e2e-distributed-pytorch-image	e2e-object-classification-distributed-pytorch	Prepare data, test and run a multi-node multi-gpu pytorch job. Use mlflow to analyze your metrics
e2e-ds-experience	e2e-ml-workflow	Create production ML pipelines with Python SDK v2 in a Jupyter notebook
get-started-notebooks	cloud-workstation	Notebook cells that accompany the Develop on cloud tutorial.
get-started-notebooks	deploy-model	Learn to deploy a model to an online endpoint, using Azure Machine Learning Python SDK v2.
get-started-notebooks	explore-data	Upload data to cloud storage, create a data asset, create new versions for data assets, use the data for interactive development.
get-started-notebooks	pipeline	Create production ML pipelines with Python SDK v2 in a Jupyter notebook
get-started-notebooks	quickstart	no description
get-started-notebooks	train-model	no description

We welcome contributions and suggestions! Please see the contributing guidelines for details.

This project has adopted the Microsoft Open Source Code of Conduct. Please see the code of conduct for details.

• Documentation