Azure Machine Learning is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions.
From a developer's perspective, I find the price of this solution high.
The licensing cost is very cheap. It's less than $50 a month.
From a developer's perspective, I find the price of this solution high.
The licensing cost is very cheap. It's less than $50 a month.
Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.
The pricing is complicated as it is based on what kind of machines you are using, the type of storage, and the kind of computation.
The support costs are 10% of the Amazon fees and it comes by default.
The pricing is complicated as it is based on what kind of machines you are using, the type of storage, and the kind of computation.
The support costs are 10% of the Amazon fees and it comes by default.
Build, deploy, and scale ML models faster, with pre-trained and custom tooling within a unified artificial intelligence platform.
The price structure is very clear
The solution's pricing is moderate.
The price structure is very clear
The solution's pricing is moderate.
Google AI Platform is a managed service that enables you to easily build machine learning models, that work on any type of data, of any size. Create your model with the powerful TensorFlow framework that powers many Google products, from Google Photos to Google Cloud Speech.
The price of the solution is competitive.
For every thousand uses, it is about four and a half euros.
The price of the solution is competitive.
For every thousand uses, it is about four and a half euros.
