Azure Machine Learning can be used for any kind of machine learning, from classical ml to deep learning, supervised, and unsupervised learning. Whether you prefer to write Python or R code or zero-code/low-code options.
Start training on your local machine and then scale out to the cloud.
The service also interoperates with popular open-source tools, such as PyTorch, TensorFlow, and scikit-learn.
Machine learning tools to fit each task
Azure Machine Learning provides all the tools developers and data scientists need for their machine learning workflows, including:
- The Azure Machine Learning designer (preview): 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.
- Visual Studio Code extension
- Machine learning CLI
- Open-source frameworks such as PyTorch, TensorFlow, and scikit-learn and many more