Azure Machine Learning can be used for any kind of machine learning, from classical ml to deep learning, supervised, and unsupervised learning. It can be used with Python or R code with the SDK or work with no-code/low-code options in the studio. One can build, train, and track machine learning and deep-learning models in an Azure Machine Learning Workspace.​​

Azure Machine Learning provides all the tools developers and data scientists need for their machine learning workflows, including:​

• The Azure Machine Learning designer: drag-n-drop modules to build your experiments and then deploy pipelines.​
• Jupyter notebooks: use our example notebooks or create your own notebooks to leverage our SDK for Python samples for your machine learning.​
• R scripts or notebooks in which you use the SDK for R to write your own code, or use the R modules in the designer.​
• The Many Models Solution Accelerator (preview) builds on Azure Machine Learning and enables you to train, operate, and manage hundreds or even thousands of machine learning models.​
• Machine learning extension for Visual Studio Code users​
• Machine learning CLI​
• Open-source frameworks such as PyTorch, TensorFlow, and scikit-learn and many more​
• Reinforcement learning with Ray RLlib​​

You have a project in mind or you have a business need ?