Azure Machine Learning Documentation
Learn how to build intelligent algorithms into apps and websites using these Azure Machine Learning products. Tutorials, quickstarts, API references, and examples show you how.
Step-by-step tutorials
Get set up and start using Azure Machine Learning service.
Use the Azure portal, an easy-to-use, no code interface to train, deploy, and manage ML models:
- Train your first experiment in visual interface's drag and drop UI
- Use automated machine learning to train and deploy your first classification model
Use the Python SDK in scripts and notebooks to train, deploy, manage ML models:
- Set up your environment & train your first ML experiment
- Train & deploy image classification models
- Prepare data and use automated ML to predict taxi fares
Consume your models:
Other Microsoft machine learning technologies
Cognitive Services
APIs that supply intelligent algorithms for your apps, websites, and bots.
Azure Machine Learning Studio
A collaborative, drag-and-drop tool to build, test, and deploy predictive analytics solutions on your data with R or Python.
SQL Server Machine Learning Services
In-database analytics with support for both R and Python.
Microsoft Machine Learning Server
Flexible enterprise machine learning platform, supporting R and Python deployments on Windows, Linux, and HDInsight Spark and Hadoop clusters.
Team Data Science Process
A collaborative data science methodology that helps teams deliver predictive analytics solutions and intelligent applications efficiently.
Data Science Virtual Machine
Experiment without installing or configuring software using the Data Science (DSVM) and Deep Learning (DLVM) virtual machines. Popular data analytics, machine learning and AI tools are preinstalled.