Machine Learning services
Bring AI to everyone with an end-to-end, scalable, trusted platform
Make better decisions, at any scale, when it matters. Bring AI everywhere to everyone using a cloud service for data scientists and developers that helps you build intelligent solutions, analyse data, build better models faster and orchestrate your machine learning development life cycle – with the confidence that your data is protected with enterprise-grade security.
Downloadable desktop application and command-line interface for Windows and MacOS. Built-in data preparation learns your data preparation steps as you perform them. Project management, run history and notebook integration bolsters your productivity. Take advantage of the best open-source frameworks, including TensorFlow, Cognitive Toolkit, Spark ML and scikit-learn.
Increase your rate of experimentation. Rapidly prototype on your desktop, then easily scale up on virtual machines or scale out using Spark clusters. Proactively manage model performance, identify the best model and promote it using data-driven insights. Collaborate and share solutions using popular Git repositories.
Deploy and manage your models everywhere. Use Docker containers to deploy models into production faster in the cloud, on premises or at the edge. Promote your best performing models into production and retrain them when their performance degrades.
Visual Studio Code Tools for AI
Build deep learning models and call services straight from your favourite IDE more easily with Azure Machine Learning services built in. Create a seamless developer experience across desktop, cloud or at the edge.
AI Toolkit for Azure IoT Edge
Bring the power of artificial intelligence and machine learning to the edge. Package pre-built models such as predictive maintenance, image classification and speech processing and deploy to IoT gateways or devices with Azure Machine Learning and Azure IoT Edge.
Quickly create powerful, highly-scalable predictive and analytical models for large image and text datasets by using deep learning and data science tools for Apache Spark.
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