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.
Quickstarts and tutorials
Get set up and start using Azure Machine Learning service:
Quickstarts:
- Run an experiment in the cloud (no install required)
- Run an experiment using a local notebook server (local SDK install)
Image classification tutorial with MNIST data:
- Part 1: Train your own model
- Part 2: Deploy that model
Regression modeling tutorial with NYC taxi data:
- Part 1: Prepare data for modeling
- Part 2: Let automated ML train models for you
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.