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Automated machine learning

Automatically build machine learning models with speed and scale

Easily build highly accurate automated machine learning models

Empower professional and nonprofessional data scientists to build machine learning models rapidly. Automate time-consuming and iterative tasks of machine learning model development using breakthrough research—and accelerate time to market.

Automatically build and deploy predictive models using the no-code UI or the SDK

Support a variety of automated machine learning tasks

Increase productivity with easy data exploration and intelligent feature engineering using deep neural networks

Build models with transparency and trust in mind using responsible machine learning solutions

Build automated ML models your way

Accelerate model creation with the automated machine learning no-code UI or SDK, or take advantage of interoperability with Microsoft Power BI, Dynamics 365, and data labelling. Build highly accurate models with automated machine learning, which makes the best selection from among a wide array of algorithms and hyperparameters. Customise your models quickly and have more control over experiment completion criteria, thresholds, validations, and blocked algorithms. Discover common errors and inconsistencies in your data through guardrails and correct them automatically.

Support a variety of machine learning tasks

Build and deploy models based on tabular, text, or image training data. Get support for common machine learning applications including classification, regression, time-series forecasting, text classification, multilabel text classification, named entity recognition, image classification, object detection, and image segmentation. Operationalize models at scale using machine learning operations (MLOps).

Improve productivity for all skill levels

Use built-in capabilities such as easy data exploration, automatic preprocessing, and intelligent feature engineering—which uses deep neural networks to handle large datasets and improve model scores—to save time and build highly accurate models. Get text data featurization in 100 languages with the included BERT deep-learning architecture. Use automated machine learning with multiple Microsoft products for faster insights regardless of machine learning skill level.

Understand models better

Better understand models and compare model performance using the built-in support for experiment run summaries and detailed metrics visualisations. Use model interpretability to evaluate ML model fit for raw and engineered features and to get insights into feature importance. Discover patterns, perform what-if analyses, and develop a deeper understanding of models to support transparency and trust in your business. Get access to the training code of the models generated.

Comprehensive security and compliance, built in

Get started with an Azure free account

Start free. Get $200 credit to use within 30 days. While you have your credit, get free amounts of many of our most popular services, plus free amounts of 40+ other services that are always free.

After your credit, move to pay as you go to keep building with the same free services. Pay only if you use more than your free monthly amounts.

After 12 months, you’ll keep getting 40+ always-free services—and still pay only for what you use beyond your free monthly amounts.

Customers using automated machine learning

Helping streaming services drive market growth

Building a new platform based on Azure Machine Learning and its automation capabilities not only helped Kantar quickly deliver accurate critical analyses and satisfy its clients, but also replaced complex, manually written Python code.

Kantar

Oriflame

"For us, each percentage increase in accuracy of the forecast might save [1] million euros. Thanks to... Azure Machine Learning, we can evaluate not 100 or 1,000 catalogs, but hundreds of thousands of options in parallel."

Jakub Orsag, IT Research and Development Manager, Oriflame
Oriflame

Schneider Electric

"With automated machine learning in Azure Machine Learning, we can focus our testing on the most accurate models and avoid testing a large range of less valuable models, because it retains only the ones we want. That saves months of time for us."

Matthieu Boujonnier, Analytics Application Architect and Data Scientist, Schneider Electric
Schneider Electric

Improving healthcare with machine learning

Stryker used automated machine learning to provide predictive-maintenance recommendations for its customers. The medical technology company can detect when certain devices are operating in a suboptimal state, even before problems occur.

Stryker

Build your machine learning skills with Azure

Learn more about machine learning on Azure and participate in hands-on tutorials with a 30-day learning journey. By the end, you'll be prepared to take the Azure Data Scientist Associate Certification.

Ready when you are—let us set up your Azure free account

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