index.md

Index

Azure Machine Learning is a cloud service that you use to train, deploy, automate, and manage machine learning models. This index should assist in navigating the Azure Machine Learning notebook samples and encourage efficient retrieval of topics and content.

Getting Started

Title	Task	Dataset	Training Compute	Deployment Target	ML Framework	Tags
Using Azure ML environments	Creating and registering environments	None	Local	None	None	None

Tutorials

Title	Task	Dataset	Training Compute	Deployment Target	ML Framework	Tags
Forecasting BikeShare Demand	Forecasting	BikeShare	Remote	None	Azure ML AutoML	Forecasting
Forecasting orange juice sales with deployment	Forecasting	Orange Juice Sales	Remote	Azure Container Instance	Azure ML AutoML	None
Forecasting orange juice sales with deployment	Forecasting	Orange Juice Sales	Remote	Azure Container Instance	Azure ML AutoML	None
Register a model and deploy locally	Deployment	None	Local	Local	None	None
⭐Data drift quickdemo	Filtering	NOAA	Remote	None	Azure ML	Dataset, Timeseries, Drift
⭐Datasets with ML Pipeline	Train	Fashion MNIST	Remote	None	Azure ML	Dataset, Pipeline, Estimator, ScriptRun
⭐Filtering data using Tabular Timeseiries Dataset related API	Filtering	NOAA	Local	None	Azure ML	Dataset, Tabular Timeseries
⭐Train with Datasets (Tabular and File)	Train	Iris, Diabetes	Remote	None	Azure ML	Dataset, Estimator, ScriptRun
Forecasting away from training data	Forecasting	None	Remote	None	Azure ML AutoML	Forecasting, Confidence Intervals
Automated ML run with basic edition features.	Classification	Bankmarketing	AML	ACI	None	featurization, explainability, remote_run, AutomatedML
Classification of credit card fraudulent transactions using Automated ML	Classification	Creditcard	AML Compute	None	None	remote_run, AutomatedML
Classification of credit card fraudulent transactions using Automated ML	Classification	Creditcard	AML Compute	None	None	AutomatedML
Automated ML run with featurization and model explainability.	Regression	MachineData	AML	ACI	None	featurization, explainability, remote_run, AutomatedML
auto-ml-forecasting-backtest-single-model		None	Remote	None	Azure ML AutoML
⭐Azure Machine Learning Pipeline with DataTranferStep	Demonstrates the use of DataTranferStep	Custom	ADF	None	Azure ML	None
Getting Started with Azure Machine Learning Pipelines	Getting Started notebook for ANML Pipelines	Custom	AML Compute	None	Azure ML	None
Azure Machine Learning Pipeline with AzureBatchStep	Demonstrates the use of AzureBatchStep	Custom	Azure Batch	None	Azure ML	None
⭐How to use ModuleStep with AML Pipelines	Demonstrates the use of ModuleStep	Custom	AML Compute	None	Azure ML	None
⭐How to use Pipeline Drafts to create a Published Pipeline	Demonstrates the use of Pipeline Drafts	Custom	AML Compute	None	Azure ML	None
⭐Azure Machine Learning Pipeline with HyperDriveStep	Demonstrates the use of HyperDriveStep	Custom	AML Compute	None	Azure ML	None
⭐How to Publish a Pipeline and Invoke the REST endpoint	Demonstrates the use of Published Pipelines	Custom	AML Compute	None	Azure ML	None
⭐How to Setup a Schedule for a Published Pipeline or Pipeline Endpoint	Demonstrates the use of Schedules for Published Pipelines and Pipeline endpoints	Custom	AML Compute	None	Azure ML	None
How to setup a versioned Pipeline Endpoint	Demonstrates the use of PipelineEndpoint to run a specific version of the Published Pipeline	Custom	AML Compute	None	Azure ML	None
⭐How to use DataPath as a PipelineParameter	Demonstrates the use of DataPath as a PipelineParameter	Custom	AML Compute	None	Azure ML	None
⭐How to use Dataset as a PipelineParameter	Demonstrates the use of Dataset as a PipelineParameter	Custom	AML Compute	None	Azure ML	None
How to use AdlaStep with AML Pipelines	Demonstrates the use of AdlaStep	Custom	Azure Data Lake Analytics	None	Azure ML	None
⭐How to use DatabricksStep with AML Pipelines	Demonstrates the use of DatabricksStep	Custom	Azure Databricks	None	Azure ML, Azure Databricks	None
⭐How to use KustoStep with AML Pipelines	Demonstrates the use of KustoStep	Custom	Kusto	None	Azure ML, Kusto	None
⭐How to use AutoMLStep with AML Pipelines	Demonstrates the use of AutoMLStep	Custom	AML Compute	None	Automated Machine Learning	None
Azure Machine Learning Pipeline with CommandStep for R	Demonstrates the use of CommandStep for running R scripts	Custom	AML Compute	None	Azure ML	None
Azure Machine Learning Pipeline with CommandStep	Demonstrates the use of CommandStep	Custom	AML Compute	None	Azure ML	None
⭐Azure Machine Learning Pipelines with Data Dependency	Demonstrates how to construct a Pipeline with data dependency between steps	Custom	AML Compute	None	Azure ML	None
How to use run a notebook as a step in AML Pipelines	Demonstrates the use of NotebookRunnerStep	Custom	AML Compute	None	Azure ML	None
Use MLflow with Azure Machine Learning to Train and Deploy Keras Image Classifier	Use MLflow with Azure Machine Learning to Train and Deploy Keras Image Classifier, leveraging MLflow auto logging	MNIST	Local, AML Compute	Azure Container Instance	Keras	mlflow, keras
Use MLflow with Azure Machine Learning to Train and Deploy PyTorch Image Classifier	Use MLflow with Azure Machine Learning to train and deploy PyTorch image classifier model	MNIST	Local, AML Compute	Azure Container Instance	PyTorch	mlflow, pytorch
Use MLflow projects with Azure Machine Learning to train a model with local compute	Use MLflow projects with Azure Machine Learning to train a model using local compute		Local		ScikitLearn	mlflow, scikit
Use MLflow projects with Azure Machine Learning to train a model	Use MLflow projects with Azure Machine Learning to train a model using azureml compute		AML Compute		Scikit	mlflow, scikit
How to use ScriptRun with data input and output	Demonstrates the use of Scriptrun with datasets	Custom	AML Compute	None	Azure ML	Dataset, ScriptRun

Training

Title	Task	Dataset	Training Compute	Deployment Target	ML Framework	Tags
Train a model with a custom Docker image	Train with custom Docker image	Oxford IIIT Pet	AML Compute	None	Pytorch	None
Train a DNN using hyperparameter tuning and deploying with Keras	Create a multi-class classifier	MNIST	AML Compute	Azure Container Instance	TensorFlow	None
Distributed training with PyTorch	Train a model using distributed training via PyTorch DistributedDataParallel	CIFAR-10	AML Compute	None	PyTorch	None
Distributed PyTorch	Train a model using the distributed training via Horovod	MNIST	AML Compute	None	PyTorch	None
Training with hyperparameter tuning using PyTorch	Train an image classification model using transfer learning with the PyTorch estimator	ImageNet	AML Compute	Azure Container Instance	PyTorch	None
Training and hyperparameter tuning with Scikit-learn	Train a support vector machine (SVM) to perform classification	Iris	AML Compute	None	Scikit-learn	None
Distributed training using TensorFlow with Horovod	Use the TensorFlow estimator to train a word2vec model	None	AML Compute	None	TensorFlow	None
Hyperparameter tuning and warm start using the TensorFlow estimator	Train a deep neural network	MNIST	AML Compute	Azure Container Instance	TensorFlow	None
Training and hyperparameter tuning using the TensorFlow estimator	Train a deep neural network	MNIST	AML Compute	Azure Container Instance	TensorFlow	None
Resuming a model	Resume a model in TensorFlow from a previously submitted run	MNIST	AML Compute	None	TensorFlow	None
Using Tensorboard	Export the run history as Tensorboard logs	None	None	None	TensorFlow	None
Training in Spark	Submiting a run on a spark cluster	None	HDI cluster	None	PySpark	None
Train on Azure Machine Learning Compute	Submit a run on Azure Machine Learning Compute.	Diabetes	AML Compute	None	None	None
Train on local compute	Train a model locally	Diabetes	Local	None	None	None
Train in a remote Linux virtual machine	Configure and execute a run	Diabetes	Data Science Virtual Machine	None	None	None
Managing your training runs	Monitor and complete runs	None	Local	None	None	None
Tensorboard integration with run history	Run a TensorFlow job and view its Tensorboard output live	None	Local, DSVM, AML Compute	None	TensorFlow	None
Use MLflow with AML for a local training run	Use MLflow tracking APIs together with Azure Machine Learning for storing your metrics and artifacts	Diabetes	Local	None	None	None
Use MLflow with AML for a remote training run	Use MLflow tracking APIs together with AML for storing your metrics and artifacts	Diabetes	AML Compute	None	None	None

Deployment

Title	Task	Dataset	Training Compute	Deployment Target	ML Framework	Tags
Train MNIST in PyTorch, convert, and deploy with ONNX Runtime	Image Classification	MNIST	AML Compute	Azure Container Instance	ONNX	ONNX Converter
Deploy ResNet50 with ONNX Runtime	Image Classification	ImageNet	Local	Azure Container Instance	ONNX	ONNX Model Zoo
⭐Convert and deploy TinyYolo with ONNX Runtime	Object Detection	PASCAL VOC	local	Azure Container Instance	ONNX	ONNX Converter

Other Notebooks

Title	Task	Dataset	Training Compute	Deployment Target	ML Framework	Tags
configuration
fairlearn-azureml-mitigation
upload-fairness-dashboard
azure-ml-with-nvidia-rapids
auto-ml-continuous-retraining
codegen-for-autofeaturization
custom-model-training-from-autofeaturization-run
auto-ml-regression-model-proxy
auto-ml-forecasting-backtest-many-models
auto-ml-forecasting-energy-demand
auto-ml-forecasting-github-dau
auto-ml-forecasting-hierarchical-timeseries
auto-ml-forecasting-many-models
auto-ml-forecasting-univariate-recipe-experiment-settings
auto-ml-forecasting-univariate-recipe-run-experiment
auto-ml-regression
automl-databricks-local-01
automl-databricks-local-with-deployment
spark_job_on_synapse_spark_pool
spark_session_on_synapse_spark_pool
Synapse_Job_Scala_Support
Synapse_Session_Scala_Support
multi-model-register-and-deploy
register-model-deploy-local-advanced
enable-app-insights-in-production-service
onnx-model-register-and-deploy
production-deploy-to-aks-ssl
production-deploy-to-aks
production-deploy-to-aks-gpu
explain-model-on-amlcompute
save-retrieve-explanations-run-history
train-explain-model-locally-and-deploy
train-explain-model-on-amlcompute-and-deploy
training_notebook
nyc-taxi-data-regression-model-building
authentication-in-azureml
pong_rllib
cartpole_ci
cartpole_sc
rai-loan-decision
Logging APIs	Logging APIs and analyzing results	None	None	None	None	None
configuration
quickstart-azureml-automl
quickstart-azureml-in-10mins
quickstart-azureml-python-sdk
tutorial-1st-experiment-sdk-train
img-classification-part1-training
img-classification-part2-deploy
img-classification-part3-deploy-encrypted
tutorial-pipeline-batch-scoring-classification
regression-automated-ml