Name	Name	Last commit message	Last commit date
parent directory ..
assets	assets
data-wrangling	data-wrangling
endpoints	endpoints
jobs	jobs
resources	resources
responsible-ai	responsible-ai
schedules	schedules
using-mlflow	using-mlflow
using-mltable	using-mltable
.gitignore	.gitignore
README.md	README.md
dev-requirements.txt	dev-requirements.txt
forecasting-requirements.txt	forecasting-requirements.txt
mlflow-requirements.txt	mlflow-requirements.txt
notebooks_config.ini	notebooks_config.ini
prefix.md	prefix.md
readme.py	readme.py
setup.sh	setup.sh
suffix.md	suffix.md

page_type

languages

products

description

sample

python

azure-machine-learning

Top-level directory for official Azure Machine Learning Python SDK v2 sample code.

Azure Machine Learning SDK (v2) examples

Prerequisites

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

Getting started

Install the SDK v2

pip install azure-ai-ml

Clone examples repository

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

Examples available

Test Status is for branch - main

Area	Sub-Area	Notebook	Description
assets	assets-in-registry	share-models-components-environments	no description
assets	component	component	Create a component asset
assets	data	data	Read, write and register a data asset
assets	data	working_with_mltable	Read, write and register a data asset
assets	environment	environment	Create custom environments from docker and/or conda YAML
assets	model	model	Create model from local files, cloud files, Runs
data-wrangling	interactive_data_wrangling.ipynb	interactive_data_wrangling	no description - This sample is excluded from automated tests
endpoints	batch	custom-output-batch	no description
endpoints	batch	imagenet-classifier-batch	no description
endpoints	batch	mlflow-for-batch-images	no description
endpoints	batch	mlflow-for-batch-tabular	no description
endpoints	batch	mnist-batch	Create and test batch endpoint and deployement
endpoints	batch	text-summarization-batch	no description
endpoints	online	online-endpoints-custom-container-multimodel	no description
endpoints	online	online-endpoints-custom-container	Deploy a custom container as an online endpoint. Use web servers other than the default Python Flask server used by Azure ML without losing the benefits of Azure ML's built-in monitoring, scaling, alerting, and authentication.
endpoints	online	online-endpoints-triton-cc	Deploy a custom container as an online endpoint. Use web servers other than the default Python Flask server used by Azure ML without losing the benefits of Azure ML's built-in monitoring, scaling, alerting, and authentication.
endpoints	online	kubernetes-online-endpoints-safe-rollout	Safely rollout a new version of a web service to production by rolling out the change to a small subset of users/requests before rolling it out completely
endpoints	online	kubernetes-online-endpoints-simple-deployment	Use an online endpoint to deploy your model, so you don't have to create and manage the underlying infrastructure
endpoints	online	debug-online-endpoints-locally-in-visual-studio-code	no description - This sample is excluded from automated tests
endpoints	online	online-endpoints-managed-identity-sai	no description
endpoints	online	online-endpoints-managed-identity-uai	no description
endpoints	online	online-endpoints-binary-payloads	no description
endpoints	online	online-endpoints-inference-schema	no description
endpoints	online	online-endpoints-keyvault	no description
endpoints	online	online-endpoints-multimodel	no description
endpoints	online	online-endpoints-openapi	no description
endpoints	online	online-endpoints-safe-rollout	Safely rollout a new version of a web service to production by rolling out the change to a small subset of users/requests before rolling it out completely
endpoints	online	online-endpoints-simple-deployment	Use an online endpoint to deploy your model, so you don't have to create and manage the underlying infrastructure
endpoints	online	online-endpoints-deploy-mlflow-model-with-script	Deploy an mlflow model to an online endpoint. This will be a no-code-deployment. It doesn't require scoring script and environment.
endpoints	online	online-endpoints-deploy-mlflow-model	Deploy an mlflow model to an online endpoint. This will be a no-code-deployment. It doesn't require scoring script and environment.
endpoints	online	online-endpoints-triton	Deploy a custom container as an online endpoint. Use web servers other than the default Python Flask server used by Azure ML without losing the benefits of Azure ML's built-in monitoring, scaling, alerting, and authentication.
jobs	automl-standalone-jobs	automl-classification-task-bankmarketing	no description
jobs	automl-standalone-jobs	mlflow-model-local-inference-test	no description - This sample is excluded from automated tests
jobs	automl-standalone-jobs	auto-ml-forecasting-github-dau	no description
jobs	automl-standalone-jobs	automl-forecasting-orange-juice-sales-mlflow	no description
jobs	automl-standalone-jobs	auto-ml-forecasting-bike-share	no description
jobs	automl-standalone-jobs	automl-forecasting-task-energy-demand-advanced	no description
jobs	automl-standalone-jobs	mlflow-model-local-inference-test	no description - This sample is excluded from automated tests
jobs	automl-standalone-jobs	automl-image-classification-multiclass-task-fridge-items	no description
jobs	automl-standalone-jobs	mlflow-model-local-inference-test	no description - This sample is excluded from automated tests
jobs	automl-standalone-jobs	automl-image-classification-multilabel-task-fridge-items	no description
jobs	automl-standalone-jobs	mlflow-model-local-inference-test	no description - This sample is excluded from automated tests
jobs	automl-standalone-jobs	automl-image-instance-segmentation-task-fridge-items	no description
jobs	automl-standalone-jobs	mlflow-model-local-inference-test	no description - This sample is excluded from automated tests
jobs	automl-standalone-jobs	image-object-detection-batch-scoring-non-mlflow-model	no description
jobs	automl-standalone-jobs	automl-image-object-detection-task-fridge-items	no description
jobs	automl-standalone-jobs	mlflow-model-local-inference-test	no description - This sample is excluded from automated tests
jobs	automl-standalone-jobs	automl-nlp-multiclass-sentiment-mlflow	no description
jobs	automl-standalone-jobs	automl-nlp-multiclass-sentiment	no description
jobs	automl-standalone-jobs	mlflow-model-local-inference-test	no description - This sample is excluded from automated tests
jobs	automl-standalone-jobs	automl-nlp-multilabel-paper-cat	no description
jobs	automl-standalone-jobs	automl-nlp-text-ner-task-distributed-with-sweeping	no description
jobs	automl-standalone-jobs	automl-nlp-text-ner-task	no description
jobs	automl-standalone-jobs	automl-regression-task-hardware-performance	no description
jobs	configuration.ipynb	configuration	Setting up your Azure Machine Learning services workspace and configuring needed resources
jobs	multicloud-configuration.ipynb	multicloud-configuration	Setting up your Azure Machine Learning services workspace and configuring needed resources - This sample is excluded from automated tests
jobs	parallel	oj_sales_prediction	Create pipeline with parallel node to do batch inference
jobs	parallel	iris_batch_prediction	Create pipeline with parallel node to do batch inference
jobs	parallel	mnist_batch_prediction	Create pipeline with parallel node to do batch inference
jobs	pipelines	pipeline_with_components_from_yaml	Create pipeline with CommandComponents from local YAML file
jobs	pipelines	pipeline_with_python_function_components	Create pipeline with command_component decorator
jobs	pipelines	pipeline_with_hyperparameter_sweep	Use sweep (hyperdrive) in pipeline to train mnist model using tensorflow
jobs	pipelines	pipeline_with_non_python_components	Create a pipeline with command function
jobs	pipelines	pipeline_with_registered_components	Register component and then use these components to build pipeline
jobs	pipelines	pipeline_with_parallel_nodes	Create pipeline with parallel node to do batch inference
jobs	pipelines	automl-classification-bankmarketing-in-pipeline	Create pipeline with automl node
jobs	pipelines	automl-forecasting-in-pipeline	no description
jobs	pipelines	automl-image-classification-multiclass-in-pipeline	Create pipeline with automl node
jobs	pipelines	automl-image-classification-multilabel-in-pipeline	Create pipeline with automl node
jobs	pipelines	automl-image-instance-segmentation-in-pipeline	Create pipeline with automl node
jobs	pipelines	automl-image-object-detection-in-pipeline	Create pipeline with automl node
jobs	pipelines	automl-regression-house-pricing-in-pipeline	Create pipeline with automl node
jobs	pipelines	automl-text-classification-in-pipeline	Create pipeline with automl node
jobs	pipelines	automl-text-classification-multilabel-in-pipeline	Create pipeline with automl node
jobs	pipelines	automl-text-ner-named-entity-recognition-in-pipeline	Create pipeline with automl node
jobs	pipelines	pipeline_with_spark_nodes	Create pipeline with spark node - This sample is excluded from automated tests
jobs	pipelines	train_mnist_with_tensorflow	Create pipeline using components to run a distributed job with tensorflow
jobs	pipelines	train_cifar_10_with_pytorch	Get data, train and evaluate a model in pipeline with Components
jobs	pipelines	nyc_taxi_data_regression	Build pipeline with components for 5 jobs - prep data, transform data, train model, predict results and evaluate model performance
jobs	pipelines	image_classification_with_densenet	Create pipeline to train cnn image classification model
jobs	pipelines	image_classification_keras_minist_convnet	Create pipeline to train cnn image classification model with keras
jobs	single-step	debug-and-monitor	Run a Command to train a basic neural network with TensorFlow on the MNIST dataset
jobs	single-step	lightgbm-iris-sweep	Run hyperparameter sweep on a Command or CommandComponent
jobs	single-step	objectdetectionAzureML	no description
jobs	single-step	tutorial	no description
jobs	single-step	distributed-cifar10	no description
jobs	single-step	pytorch-iris	Run Command to train a neural network with PyTorch on Iris dataset
jobs	single-step	train-hyperparameter-tune-deploy-with-pytorch	Train, hyperparameter tune, and deploy a PyTorch model to classify chicken and turkey images to build a deep learning neural network (DNN) based on PyTorch's transfer learning tutorial.
jobs	single-step	accident-prediction	Run R in a Command to train a prediction model
jobs	single-step	sklearn-diabetes	Run Command to train a scikit-learn LinearRegression model on the Diabetes dataset
jobs	single-step	iris-scikit-learn	Run Command to train a scikit-learn SVM on the Iris dataset
jobs	single-step	sklearn-mnist	Run a Command to train a scikit-learn SVM on the mnist dataset.
jobs	single-step	train-hyperparameter-tune-with-sklearn	Train and tune a machine learning model using scikit-learn training scripts to build a to classify iris flower images. - This sample is excluded from automated tests
jobs	single-step	tensorflow-mnist-distributed-horovod	Run a Distributed Command to train a basic neural network with distributed MPI on the MNIST dataset using Horovod
jobs	single-step	tensorflow-mnist-distributed	Run a Distributed Command to train a basic neural network with TensorFlow on the MNIST dataset
jobs	single-step	tensorflow-mnist	Run a Command to train a basic neural network with TensorFlow on the MNIST dataset
jobs	single-step	train-hyperparameter-tune-deploy-with-keras	Train, hyperparameter tune, and deploy a Keras model to classify handwritten digits using a deep neural network (DNN). - This sample is excluded from automated tests
jobs	single-step	train-hyperparameter-tune-deploy-with-tensorflow	Train, hyperparameter tune, and deploy a Tensorflow model to classify handwritten digits using a deep neural network (DNN). - This sample is excluded from automated tests
jobs	spark	submit_spark_pipeline_jobs	no description - This sample is excluded from automated tests
jobs	spark	submit_spark_standalone_jobs	no description - This sample is excluded from automated tests
resources	compute	attach_manage_spark_pools	no description - This sample is excluded from automated tests
resources	compute	compute	Create compute in Azure ML workspace
resources	connections	connections	no description
resources	datastores	datastore	Create datastores and use in a Command - This sample is excluded from automated tests
resources	registry	registry-create	no description
resources	workspace	workspace	Create Azure ML workspace
responsible-ai	responsibleaidashboard-diabetes-decision-making	responsibleaidashboard-diabetes-decision-making	no description
responsible-ai	responsibleaidashboard-diabetes-regression-model-debugging	responsibleaidashboard-diabetes-regression-model-debugging	no description
responsible-ai	responsibleaidashboard-housing-classification-model-debugging	responsibleaidashboard-housing-classification-model-debugging	no description
responsible-ai	responsibleaidashboard-housing-decision-making	responsibleaidashboard-housing-decision-making	no description
responsible-ai	responsibleaidashboard-programmer-regression-model-debugging	responsibleaidashboard-programmer-regression-model-debugging	no description
schedules	job-schedule.ipynb	job-schedule	Create a component asset
using-mlflow	deploy	mlflow_sdk_online_endpoints	no description - This sample is excluded from automated tests
using-mlflow	deploy	mlflow_sdk_online_endpoints_progresive	no description - This sample is excluded from automated tests
using-mlflow	deploy	mlflow_sdk_web_service	no description - This sample is excluded from automated tests
using-mlflow	deploy	scoring_to_mlmodel	no description - This sample is excluded from automated tests
using-mlflow	deploy	track_with_databricks_deploy_aml	no description - This sample is excluded from automated tests
using-mlflow	model-management	model_management	no description - This sample is excluded from automated tests
using-mlflow	runs-management	run_history	no description - This sample is excluded from automated tests
using-mlflow	train-and-log	keras_mnist_with_mlflow	no description - This sample is excluded from automated tests
using-mlflow	train-and-log	logging_and_customizing_models	no description - This sample is excluded from automated tests
using-mlflow	train-and-log	xgboost_classification_mlflow	no description - This sample is excluded from automated tests
using-mlflow	train-and-log	xgboost_nested_runs	no description - This sample is excluded from automated tests
using-mlflow	train-and-log	xgboost_service_principal	no description - This sample is excluded from automated tests
using-mlflow	using-rest-api	using_mlflow_rest_api	no description - This sample is excluded from automated tests
using-mltable	local-to-cloud	mltable-local-to-cloud	no description
using-mltable	quickstart	mltable-quickstart	no description