Azure Machine Learning vs NanoNets: What are the differences?
Azure Machine Learning: 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; NanoNets: Machine learning API with less data. Build a custom machine learning model without expertise or large amount of data. Just go to nanonets, upload images, wait for few minutes and integrate nanonets API to your application.
Azure Machine Learning and NanoNets can be primarily classified 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, NanoNets provides the following key features:
- Image categorization API with less than 30 images per category
- Custom object localization API
- Text deduplication API