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README.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

code style: black license: MIT

Prerequisites

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

Getting started

  1. 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 Status
assets assets-in-registry share-data-using-registry no description share-data-using-registry
assets assets-in-registry share-models-components-environments no description share-models-components-environments
assets component component Create a component asset component
assets data data Read, write and register a data asset data
assets data working_with_mltable Read, write and register a data asset working_with_mltable
assets environment environment Create custom environments from docker and/or conda YAML environment
assets model model Create model from local files, cloud files, Runs model
data-wrangling interactive_data_wrangling.ipynb interactive_data_wrangling no description - This sample is excluded from automated tests interactive_data_wrangling
endpoints batch custom-output-batch no description custom-output-batch
endpoints batch mlflow-for-batch-tabular no description mlflow-for-batch-tabular
endpoints batch text-summarization-batch no description text-summarization-batch
endpoints batch imagenet-classifier-batch no description imagenet-classifier-batch
endpoints batch imagenet-classifier-mlflow no description imagenet-classifier-mlflow
endpoints batch mnist-batch Create and test batch endpoint and deployement mnist-batch
endpoints batch sdk-deploy-and-test no description sdk-deploy-and-test
endpoints batch sdk-deploy-and-test no description sdk-deploy-and-test
endpoints batch sdk-deploy-and-test no description sdk-deploy-and-test
endpoints online online-endpoints-custom-container-multimodel no description online-endpoints-custom-container-multimodel
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. online-endpoints-custom-container
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. online-endpoints-triton-cc
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 kubernetes-online-endpoints-safe-rollout
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 kubernetes-online-endpoints-simple-deployment
endpoints online 1_langchain_basic_deploy Use an online endpoint to deploy a Langchain application, combining the power of LLMs with Azure ML's inferencing management. 1_langchain_basic_deploy
endpoints online 1_semantic_http_server Use an online endpoint to deploy a Semantic Kernel application, combining the power of LLMs with Azure ML's inferencing management. 1_semantic_http_server
endpoints online debug-online-endpoints-locally-in-visual-studio-code no description - This sample is excluded from automated tests debug-online-endpoints-locally-in-visual-studio-code
endpoints online online-endpoints-managed-identity-sai no description online-endpoints-managed-identity-sai
endpoints online online-endpoints-managed-identity-uai no description online-endpoints-managed-identity-uai
endpoints online online-endpoints-binary-payloads no description online-endpoints-binary-payloads
endpoints online online-endpoints-inference-schema no description online-endpoints-inference-schema
endpoints online online-endpoints-keyvault no description online-endpoints-keyvault
endpoints online online-endpoints-multimodel no description online-endpoints-multimodel
endpoints online online-endpoints-openapi no description online-endpoints-openapi
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 online-endpoints-safe-rollout
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 online-endpoints-simple-deployment
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. online-endpoints-deploy-mlflow-model-with-script
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. online-endpoints-deploy-mlflow-model
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. online-endpoints-triton
featurestore_sample notebooks [1. Develop a feature set and register with managed feature store](featurestore_sample/notebooks/sdk_and_cli/1. Develop a feature set and register with managed feature store.ipynb) no description [![1. Develop a feature set and register with managed feature store](https://github.com/Azure/azureml-examples/actions/workflows/sdk-featurestore_sample-notebooks-sdk_and_cli-1. Develop a feature set and register with managed feature store.yml/badge.svg?branch=main)](https://github.com/Azure/azureml-examples/actions/workflows/sdk-featurestore_sample-notebooks-sdk_and_cli-1. Develop a feature set and register with managed feature store.yml)
featurestore_sample notebooks [2. Enable materialization and backfill feature data](featurestore_sample/notebooks/sdk_and_cli/2. Enable materialization and backfill feature data.ipynb) no description [![2. Enable materialization and backfill feature data](https://github.com/Azure/azureml-examples/actions/workflows/sdk-featurestore_sample-notebooks-sdk_and_cli-2. Enable materialization and backfill feature data.yml/badge.svg?branch=main)](https://github.com/Azure/azureml-examples/actions/workflows/sdk-featurestore_sample-notebooks-sdk_and_cli-2. Enable materialization and backfill feature data.yml)
featurestore_sample notebooks [3. Experiment and train models using features](featurestore_sample/notebooks/sdk_and_cli/3. Experiment and train models using features.ipynb) no description [![3. Experiment and train models using features](https://github.com/Azure/azureml-examples/actions/workflows/sdk-featurestore_sample-notebooks-sdk_and_cli-3. Experiment and train models using features.yml/badge.svg?branch=main)](https://github.com/Azure/azureml-examples/actions/workflows/sdk-featurestore_sample-notebooks-sdk_and_cli-3. Experiment and train models using features.yml)
featurestore_sample notebooks [4. Enable recurrent materialization and run batch inference](featurestore_sample/notebooks/sdk_and_cli/4. Enable recurrent materialization and run batch inference.ipynb) no description [![4. Enable recurrent materialization and run batch inference](https://github.com/Azure/azureml-examples/actions/workflows/sdk-featurestore_sample-notebooks-sdk_and_cli-4. Enable recurrent materialization and run batch inference.yml/badge.svg?branch=main)](https://github.com/Azure/azureml-examples/actions/workflows/sdk-featurestore_sample-notebooks-sdk_and_cli-4. Enable recurrent materialization and run batch inference.yml)
featurestore_sample notebooks [Network Isolation for Feature store](featurestore_sample/notebooks/sdk_and_cli/network_isolation/Network Isolation for Feature store.ipynb) no description [![Network Isolation for Feature store](https://github.com/Azure/azureml-examples/actions/workflows/sdk-featurestore_sample-notebooks-sdk_and_cli-network_isolation-Network Isolation for Feature store.yml/badge.svg?branch=main)](https://github.com/Azure/azureml-examples/actions/workflows/sdk-featurestore_sample-notebooks-sdk_and_cli-network_isolation-Network Isolation for Feature store.yml)
featurestore_sample notebooks [1. Develop a feature set and register with managed feature store](featurestore_sample/notebooks/sdk_only/1. Develop a feature set and register with managed feature store.ipynb) no description [![1. Develop a feature set and register with managed feature store](https://github.com/Azure/azureml-examples/actions/workflows/sdk-featurestore_sample-notebooks-sdk_only-1. Develop a feature set and register with managed feature store.yml/badge.svg?branch=main)](https://github.com/Azure/azureml-examples/actions/workflows/sdk-featurestore_sample-notebooks-sdk_only-1. Develop a feature set and register with managed feature store.yml)
featurestore_sample notebooks [2. Enable materialization and backfill feature data](featurestore_sample/notebooks/sdk_only/2. Enable materialization and backfill feature data.ipynb) no description [![2. Enable materialization and backfill feature data](https://github.com/Azure/azureml-examples/actions/workflows/sdk-featurestore_sample-notebooks-sdk_only-2. Enable materialization and backfill feature data.yml/badge.svg?branch=main)](https://github.com/Azure/azureml-examples/actions/workflows/sdk-featurestore_sample-notebooks-sdk_only-2. Enable materialization and backfill feature data.yml)
featurestore_sample notebooks [3. Experiment and train models using features](featurestore_sample/notebooks/sdk_only/3. Experiment and train models using features.ipynb) no description [![3. Experiment and train models using features](https://github.com/Azure/azureml-examples/actions/workflows/sdk-featurestore_sample-notebooks-sdk_only-3. Experiment and train models using features.yml/badge.svg?branch=main)](https://github.com/Azure/azureml-examples/actions/workflows/sdk-featurestore_sample-notebooks-sdk_only-3. Experiment and train models using features.yml)
featurestore_sample notebooks [4. Enable recurrent materialization and run batch inference](featurestore_sample/notebooks/sdk_only/4. Enable recurrent materialization and run batch inference.ipynb) no description [![4. Enable recurrent materialization and run batch inference](https://github.com/Azure/azureml-examples/actions/workflows/sdk-featurestore_sample-notebooks-sdk_only-4. Enable recurrent materialization and run batch inference.yml/badge.svg?branch=main)](https://github.com/Azure/azureml-examples/actions/workflows/sdk-featurestore_sample-notebooks-sdk_only-4. Enable recurrent materialization and run batch inference.yml)
foundation-models azure_openai openai_completions_finetune no description openai_completions_finetune
foundation-models huggingface question-answering-online-endpoint no description question-answering-online-endpoint
foundation-models huggingface text-generation-streaming-online-endpoint no description text-generation-streaming-online-endpoint
foundation-models huggingface token-classification-online-endpoint no description token-classification-online-endpoint
foundation-models huggingface translation-online-endpoint no description translation-online-endpoint
foundation-models huggingface zero-shot-classification-online-endpoint no description zero-shot-classification-online-endpoint
foundation-models system fill-mask no description fill-mask
foundation-models system question-answering no description question-answering
foundation-models system abstractive-and-extractive-summarization no description abstractive-and-extractive-summarization
foundation-models system entailment-contradiction no description entailment-contradiction
foundation-models system sentiment-analysis no description sentiment-analysis
foundation-models system text-generation no description text-generation
foundation-models system news-articles-entity-recognition no description news-articles-entity-recognition
foundation-models system translation-romanian-to-english no description translation-romanian-to-english
foundation-models system extractive-qa no description extractive-qa
foundation-models system news-summary no description news-summary
foundation-models system emotion-detection no description emotion-detection
foundation-models system token-classification no description token-classification
foundation-models system translation no description translation
foundation-models system import_model_into_registry no description import_model_into_registry
foundation-models system asr-batch-endpoint no description asr-batch-endpoint
foundation-models system asr-online-endpoint no description asr-online-endpoint
foundation-models system fill-mask-batch-endpoint no description fill-mask-batch-endpoint
foundation-models system fill-mask-online-endpoint no description fill-mask-online-endpoint
foundation-models system question-answering-batch-endpoint no description question-answering-batch-endpoint
foundation-models system question-answering-online-endpoint no description question-answering-online-endpoint
foundation-models system summarization-batch-endpoint no description summarization-batch-endpoint
foundation-models system summarization-online-endpoint no description summarization-online-endpoint
foundation-models system entailment-contradiction-batch no description entailment-contradiction-batch
foundation-models system text-classification-online-endpoint no description text-classification-online-endpoint
foundation-models system llama-prepare-uai no description llama-prepare-uai
foundation-models system llama-safe-batch-deployment no description llama-safe-batch-deployment
foundation-models system llama-safe-online-deployment no description llama-safe-online-deployment
foundation-models system text-generation-batch-endpoint no description text-generation-batch-endpoint
foundation-models system text-generation-online-endpoint-dolly no description text-generation-online-endpoint-dolly
foundation-models system text-generation-online-endpoint no description text-generation-online-endpoint
foundation-models system token-classification-batch-endpoint no description token-classification-batch-endpoint
foundation-models system token-classification-online-endpoint no description token-classification-online-endpoint
foundation-models system translation-batch-endpoint no description translation-batch-endpoint
foundation-models system translation-online-endpoint no description translation-online-endpoint
generative-ai promptflow create_faiss_index no description create_faiss_index
generative-ai rag acs_mlindex_with_langchain no description acs_mlindex_with_langchain
generative-ai rag s3_to_acs_mlindex_with_langchain no description s3_to_acs_mlindex_with_langchain
generative-ai rag db_copilot_with_rag no description db_copilot_with_rag
generative-ai rag faiss_mlindex_with_langchain no description faiss_mlindex_with_langchain
generative-ai rag scheduled_update_faiss_index no description scheduled_update_faiss_index
generative-ai rag url_to_faiss_incremental_embeddings_with_tabular_data no description url_to_faiss_incremental_embeddings_with_tabular_data
generative-ai rag mlindex_with_testgen_autoprompt no description mlindex_with_testgen_autoprompt
generative-ai rag qa_data_generation no description qa_data_generation
jobs automl-standalone-jobs automl-classification-task-bankmarketing-serverless no description automl-classification-task-bankmarketing-serverless
jobs automl-standalone-jobs automl-classification-task-bankmarketing no description automl-classification-task-bankmarketing
jobs automl-standalone-jobs mlflow-model-local-inference-test no description - This sample is excluded from automated tests mlflow-model-local-inference-test
jobs automl-standalone-jobs automl-forecasting-distributed-tcn no description automl-forecasting-distributed-tcn
jobs automl-standalone-jobs auto-ml-forecasting-github-dau no description auto-ml-forecasting-github-dau
jobs automl-standalone-jobs automl-forecasting-orange-juice-sales-mlflow no description automl-forecasting-orange-juice-sales-mlflow
jobs automl-standalone-jobs automl-forecasting-recipe-univariate-experiment-settings no description automl-forecasting-recipe-univariate-experiment-settings
jobs automl-standalone-jobs automl-forecasting-recipe-univariate-run no description automl-forecasting-recipe-univariate-run
jobs automl-standalone-jobs auto-ml-forecasting-bike-share no description auto-ml-forecasting-bike-share
jobs automl-standalone-jobs automl-forecasting-task-energy-demand-advanced-mlflow no description automl-forecasting-task-energy-demand-advanced-mlflow
jobs automl-standalone-jobs automl-forecasting-task-energy-demand-advanced no description automl-forecasting-task-energy-demand-advanced
jobs automl-standalone-jobs mlflow-model-local-inference-test no description - This sample is excluded from automated tests mlflow-model-local-inference-test
jobs automl-standalone-jobs automl-image-classification-multiclass-task-fridge-items no description automl-image-classification-multiclass-task-fridge-items
jobs automl-standalone-jobs mlflow-model-local-inference-test no description - This sample is excluded from automated tests mlflow-model-local-inference-test
jobs automl-standalone-jobs automl-image-classification-multilabel-task-fridge-items no description automl-image-classification-multilabel-task-fridge-items
jobs automl-standalone-jobs mlflow-model-local-inference-test no description - This sample is excluded from automated tests mlflow-model-local-inference-test
jobs automl-standalone-jobs automl-image-instance-segmentation-task-fridge-items no description automl-image-instance-segmentation-task-fridge-items
jobs automl-standalone-jobs mlflow-model-local-inference-test no description - This sample is excluded from automated tests mlflow-model-local-inference-test
jobs automl-standalone-jobs odFridgeObjects_jsonl2coco no description odFridgeObjects_jsonl2coco
jobs automl-standalone-jobs image-object-detection-batch-scoring-non-mlflow-model no description image-object-detection-batch-scoring-non-mlflow-model
jobs automl-standalone-jobs automl-image-object-detection-task-fridge-items no description automl-image-object-detection-task-fridge-items
jobs automl-standalone-jobs mlflow-model-local-inference-test no description - This sample is excluded from automated tests mlflow-model-local-inference-test
jobs automl-standalone-jobs automl-nlp-multiclass-sentiment-mlflow no description automl-nlp-multiclass-sentiment-mlflow
jobs automl-standalone-jobs automl-nlp-multiclass-sentiment no description automl-nlp-multiclass-sentiment
jobs automl-standalone-jobs mlflow-model-local-inference-test no description - This sample is excluded from automated tests mlflow-model-local-inference-test
jobs automl-standalone-jobs automl-nlp-multilabel-paper-cat no description automl-nlp-multilabel-paper-cat
jobs automl-standalone-jobs automl-nlp-text-ner-task-distributed-with-sweeping no description automl-nlp-text-ner-task-distributed-with-sweeping
jobs automl-standalone-jobs automl-nlp-text-ner-task no description automl-nlp-text-ner-task
jobs automl-standalone-jobs automl-regression-task-hardware-performance no description automl-regression-task-hardware-performance
jobs configuration.ipynb configuration Setting up your Azure Machine Learning services workspace and configuring needed resources configuration
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 multicloud-configuration
jobs parallel oj_sales_prediction Create pipeline with parallel node to do batch inference oj_sales_prediction
jobs parallel iris_batch_prediction Create pipeline with parallel node to do batch inference iris_batch_prediction
jobs parallel mnist_batch_prediction Create pipeline with parallel node to do batch inference mnist_batch_prediction
jobs pipelines pipeline_with_components_from_yaml Create pipeline with CommandComponents from local YAML file pipeline_with_components_from_yaml
jobs pipelines pipeline_with_components_from_yaml_serverless Create pipeline with CommandComponents from local YAML file pipeline_with_components_from_yaml_serverless
jobs pipelines pipeline_with_python_function_components Create pipeline with command_component decorator pipeline_with_python_function_components
jobs pipelines pipeline_with_hyperparameter_sweep Use sweep (hyperdrive) in pipeline to train mnist model using tensorflow pipeline_with_hyperparameter_sweep
jobs pipelines pipeline_with_non_python_components Create a pipeline with command function pipeline_with_non_python_components
jobs pipelines pipeline_with_registered_components Register component and then use these components to build pipeline pipeline_with_registered_components
jobs pipelines pipeline_with_parallel_nodes Create pipeline with parallel node to do batch inference pipeline_with_parallel_nodes
jobs pipelines automl-classification-bankmarketing-in-pipeline Create pipeline with automl node automl-classification-bankmarketing-in-pipeline
jobs pipelines automl-forecasting-in-pipeline no description automl-forecasting-in-pipeline
jobs pipelines automl-image-classification-multiclass-in-pipeline Create pipeline with automl node automl-image-classification-multiclass-in-pipeline
jobs pipelines automl-image-classification-multilabel-in-pipeline Create pipeline with automl node automl-image-classification-multilabel-in-pipeline
jobs pipelines automl-image-instance-segmentation-in-pipeline Create pipeline with automl node automl-image-instance-segmentation-in-pipeline
jobs pipelines automl-image-object-detection-in-pipeline Create pipeline with automl node automl-image-object-detection-in-pipeline
jobs pipelines automl-regression-house-pricing-in-pipeline Create pipeline with automl node automl-regression-house-pricing-in-pipeline
jobs pipelines automl-text-classification-in-pipeline Create pipeline with automl node automl-text-classification-in-pipeline
jobs pipelines automl-text-classification-multilabel-in-pipeline Create pipeline with automl node automl-text-classification-multilabel-in-pipeline
jobs pipelines automl-text-ner-named-entity-recognition-in-pipeline Create pipeline with automl node automl-text-ner-named-entity-recognition-in-pipeline
jobs pipelines pipeline_with_spark_nodes Create pipeline with spark node pipeline_with_spark_nodes
jobs pipelines nyc_taxi_data_regression_with_pipeline_component Create pipeline with CommandComponents from local YAML file nyc_taxi_data_regression_with_pipeline_component
jobs pipelines pipeline_with_train_eval_pipeline_component Create pipeline with CommandComponents from local YAML file pipeline_with_train_eval_pipeline_component
jobs pipelines automl-forecasting-demand-hierarchical-timeseries-in-pipeline no description automl-forecasting-demand-hierarchical-timeseries-in-pipeline
jobs pipelines automl-forecasting-demand-many-models-in-pipeline no description automl-forecasting-demand-many-models-in-pipeline
jobs pipelines train_mnist_with_tensorflow Create pipeline using components to run a distributed job with tensorflow train_mnist_with_tensorflow
jobs pipelines train_cifar_10_with_pytorch Get data, train and evaluate a model in pipeline with Components train_cifar_10_with_pytorch
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 nyc_taxi_data_regression
jobs pipelines image_classification_with_densenet Create pipeline to train cnn image classification model image_classification_with_densenet
jobs pipelines image_classification_keras_minist_convnet Create pipeline to train cnn image classification model with keras image_classification_keras_minist_convnet
jobs single-step debug-and-monitor Run a Command to train a basic neural network with TensorFlow on the MNIST dataset debug-and-monitor
jobs single-step lightgbm-iris-sweep Run hyperparameter sweep on a Command or CommandComponent lightgbm-iris-sweep
jobs single-step objectdetectionAzureML no description objectdetectionAzureML
jobs single-step tutorial no description tutorial
jobs single-step distributed-cifar10 no description distributed-cifar10
jobs single-step pytorch-iris Run Command to train a neural network with PyTorch on Iris dataset pytorch-iris
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. train-hyperparameter-tune-deploy-with-pytorch
jobs single-step accident-prediction Run R in a Command to train a prediction model accident-prediction
jobs single-step sklearn-diabetes Run Command to train a scikit-learn LinearRegression model on the Diabetes dataset sklearn-diabetes
jobs single-step iris-scikit-learn Run Command to train a scikit-learn SVM on the Iris dataset iris-scikit-learn
jobs single-step sklearn-mnist Run a Command to train a scikit-learn SVM on the mnist dataset. sklearn-mnist
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 train-hyperparameter-tune-with-sklearn
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 tensorflow-mnist-distributed-horovod
jobs single-step tensorflow-mnist-distributed Run a Distributed Command to train a basic neural network with TensorFlow on the MNIST dataset tensorflow-mnist-distributed
jobs single-step tensorflow-mnist Run a Command to train a basic neural network with TensorFlow on the MNIST dataset tensorflow-mnist
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 train-hyperparameter-tune-deploy-with-keras
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 train-hyperparameter-tune-deploy-with-tensorflow
jobs spark run_interactive_session_notebook no description run_interactive_session_notebook
jobs spark submit_spark_pipeline_jobs no description submit_spark_pipeline_jobs
jobs spark submit_spark_standalone_jobs no description submit_spark_standalone_jobs
jobs spark submit_spark_standalone_jobs_managed_vnet no description submit_spark_standalone_jobs_managed_vnet
resources compute attach_manage_spark_pools no description attach_manage_spark_pools
resources compute compute Create compute in Azure ML workspace compute
resources connections connections no description connections
resources datastores datastore Create datastores and use in a Command - This sample is excluded from automated tests datastore
resources registry registry-create no description registry-create
resources workspace workspace Create Azure ML workspace workspace
responsible-ai tabular responsibleaidashboard-diabetes-decision-making no description responsibleaidashboard-diabetes-decision-making
responsible-ai tabular responsibleaidashboard-diabetes-regression-model-debugging no description responsibleaidashboard-diabetes-regression-model-debugging
responsible-ai tabular responsibleaidashboard-housing-classification-model-debugging no description responsibleaidashboard-housing-classification-model-debugging
responsible-ai tabular responsibleaidashboard-housing-decision-making no description responsibleaidashboard-housing-decision-making
responsible-ai tabular responsibleaidashboard-programmer-regression-model-debugging no description responsibleaidashboard-programmer-regression-model-debugging
responsible-ai text responsibleaidashboard-multilabel-text-classification-covid-events no description responsibleaidashboard-multilabel-text-classification-covid-events
responsible-ai text responsibleaidashboard-text-classification-DBPedia no description responsibleaidashboard-text-classification-DBPedia
responsible-ai text responsibleaidashboard-text-classification-blbooksgenre no description responsibleaidashboard-text-classification-blbooksgenre
responsible-ai vision responsibleaidashboard-automl-image-classification-fridge no description responsibleaidashboard-automl-image-classification-fridge
responsible-ai vision responsibleaidashboard-image-classification-fridge no description responsibleaidashboard-image-classification-fridge
responsible-ai vision responsibleaidashboard-image-multilabel-classification-fridge no description responsibleaidashboard-image-multilabel-classification-fridge
responsible-ai vision responsibleaidashboard-object-detection-MSCOCO no description responsibleaidashboard-object-detection-MSCOCO
schedules job-schedule.ipynb job-schedule Create a component asset job-schedule
using-mlflow deploy mlflow_sdk_online_endpoints no description - This sample is excluded from automated tests mlflow_sdk_online_endpoints
using-mlflow deploy mlflow_sdk_online_endpoints_progresive no description - This sample is excluded from automated tests mlflow_sdk_online_endpoints_progresive
using-mlflow deploy mlflow_sdk_web_service no description - This sample is excluded from automated tests mlflow_sdk_web_service
using-mlflow deploy scoring_to_mlmodel no description - This sample is excluded from automated tests scoring_to_mlmodel
using-mlflow deploy track_with_databricks_deploy_aml no description - This sample is excluded from automated tests track_with_databricks_deploy_aml
using-mlflow model-management model_management no description - This sample is excluded from automated tests model_management
using-mlflow runs-management run_history no description - This sample is excluded from automated tests run_history
using-mlflow train-and-log keras_mnist_with_mlflow no description - This sample is excluded from automated tests keras_mnist_with_mlflow
using-mlflow train-and-log logging_and_customizing_models no description - This sample is excluded from automated tests logging_and_customizing_models
using-mlflow train-and-log xgboost_classification_mlflow no description - This sample is excluded from automated tests xgboost_classification_mlflow
using-mlflow train-and-log xgboost_nested_runs no description - This sample is excluded from automated tests xgboost_nested_runs
using-mlflow train-and-log xgboost_service_principal no description - This sample is excluded from automated tests xgboost_service_principal
using-mlflow using-rest-api using_mlflow_rest_api no description - This sample is excluded from automated tests using_mlflow_rest_api
using-mltable delimited-files-example delimited-files-example no description delimited-files-example
using-mltable delta-lake-example delta-lake-example no description delta-lake-example
using-mltable from-paths-example from-paths-example no description from-paths-example
using-mltable local-to-cloud mltable-local-to-cloud no description mltable-local-to-cloud
using-mltable quickstart mltable-quickstart no description mltable-quickstart

Contributing

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

Code of Conduct

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

Reference