Azure Machine Learning vs Gradient°: What are the differences?
Developers describe Azure Machine Learning as "A fully-managed cloud service for predictive analytics". Azure Machine Learning is a fully-managed cloud service that enables data scientists and developers to efficiently embed predictive analytics into their applications, helping organizations use massive data sets and bring all the benefits of the cloud to machine learning. On the other hand, Gradient° is detailed as "Deep learning platform built for developers". Gradient° is a suite of tools for exploring data and training neural networks. Gradient° includes 1-click Jupyter notebooks, a powerful job runner, and a python module to run any code on a fully managed GPU cluster in the cloud. Gradient is also rolling out full support for Google's new TPUv2 accelerator to power even more newer workflows.
Azure Machine Learning and Gradient° can be categorized as "Machine Learning as a Service" tools.
Some of the features offered by Azure Machine Learning are:
- Designed for new and experienced users
- Proven algorithms from MS Research, Xbox and Bing
- First class support for the open source language R
On the other hand, Gradient° provides the following key features:
- 1-click Jupyter notebooks
- a powerful job runner
- Python module to run any code on a fully managed GPU cluster in the cloud