Microsoft Azure Machine Learning Studio and Google Cloud AI Platform compete in the cloud-based machine learning services category. Microsoft Azure Machine Learning Studio has the upper hand for its ease of use, especially for users without extensive programming expertise.
Features: Microsoft Azure Machine Learning Studio offers drag-and-drop capabilities, integration with R and Python, and ease of PowerPoint report creation. Google Cloud AI Platform is equipped with video and object classification capabilities, Firebase, and BigQuery integration.
Room for Improvement: Microsoft Azure Machine Learning Studio could benefit from more advanced algorithms, better integration with non-Microsoft services, and enhanced data transformation. Google Cloud AI Platform users desire more accessible model management, text extraction improvements, and easier integration between different environments.
Ease of Deployment and Customer Service: Microsoft Azure Machine Learning Studio mostly uses public cloud environments with some hybrid and on-premises deployments, with generally well-regarded customer support although with some feedback on slow escalation to higher-tier support. Google Cloud AI Platform also predominantly uses the public cloud and is praised for its documentation, but direct technical support details are less documented.
Pricing and ROI: Microsoft Azure Machine Learning Studio offers a pay-as-you-go model that can become costly without careful resource management, considered less straightforward but with notable ROI potential if optimized. Google Cloud AI Platform provides competitive pricing with an attractive starting program, though it could benefit from clearer pricing and model management features.
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.
Azure Machine Learning is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions.
It has everything you need to create complete predictive analytics solutions in the cloud, from a large algorithm library, to a studio for building models, to an easy way to deploy your model as a web service. Quickly create, test, operationalize, and manage predictive models.
Microsoft Azure Machine Learning Will Help You:
With Microsoft Azure Machine Learning You Can:
Microsoft Azure Machine Learning Features:
Microsoft Azure Machine Learning Benefits:
Reviews from Real Users:
"The ability to do the templating and be able to transfer it so that I can easily do multiple types of models and data mining is a valuable aspect of this solution. You only have to set up the flows, the templates, and the data once and then you can make modifications and test different segmentations throughout.” - Channing S.l, Owner at Channing Stowell Associates
"The most valuable feature is the knowledge bank, which allows us to ask questions and the AI will automatically pull the pre-prescribed responses.” - Chris P., Tech Lead at a tech services company
"The UI is very user-friendly and the AI is easy to use.” - Mikayil B., CRM Consultant at a computer software company
"The solution is very fast and simple for a data science solution.” - Omar A., Big Data & Cloud Manager at a tech services company
We monitor all AI Development Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.