Compare Caffe vs. Microsoft Azure Machine Learning Studio

Caffe is ranked 5th in AI Development Platforms while Microsoft Azure Machine Learning Studio is ranked 1st in AI Development Platforms with 5 reviews. Caffe is rated 0, while Microsoft Azure Machine Learning Studio is rated 7.4. On the other hand, the top reviewer of Microsoft Azure Machine Learning Studio writes "Enables quick creation of models for PoC in predictive analysis, but needs better ensemble modeling". Caffe is most compared with TensorFlow, whereas Microsoft Azure Machine Learning Studio is most compared with Databricks, Amazon SageMaker and Alteryx.
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To use MLS is fairly cheap. Even the paid account is something like $20/month, unless you are provisioning large numbers of VMs for a Hadoop cluster. The main MS makes money with this solution is forcing the user to deploy their model on REST API, and being charged each time the API is accessed. There are several pricing tiers for the API. If you do not use the API, then value of MLS is to create rapid experiments ($20/month). The resulting model is not exportable to use, thus you’ll have to recreate the algorithms in either R or Python, which is what I did. MLS results gave me a direction to work with, the actual work is mostly done in R and Python outside of MLS.

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Views
8,698
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7,302
Reviews
5
Average Words per Review
353
Avg. Rating
7.4
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Also Known As
Azure Machine Learning
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Caffe
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Microsoft
Overview

Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors.

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.

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