Google Cloud Datalab vs. Microsoft Azure Machine Learning Studio

As of June 2019, Google Cloud Datalab is ranked 19th in Data Science Platforms vs Microsoft Azure Machine Learning Studio which is ranked 4th in Data Science Platforms with 6 reviews. 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". Google Cloud Datalab is most compared with Databricks, Amazon SageMaker and Tableau. Microsoft Azure Machine Learning Studio is most compared with Databricks, KNIME and Amazon SageMaker.
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Pricing and Cost Advice
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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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Ranking
19th
Views
1,040
Comparisons
863
Reviews
0
Average Words per Review
0
Avg. Rating
N/A
4th
Views
7,379
Comparisons
6,240
Reviews
6
Average Words per Review
341
Avg. Rating
7.5
Top Comparisons
Compared 33% of the time.
Compared 18% of the time.
Also Known As
Azure Machine Learning
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Overview

Cloud Datalab is a powerful interactive tool created to explore, analyze, transform and visualize data and build machine learning models on Google Cloud Platform. It runs on Google Compute Engine and connects to multiple cloud services easily so you can focus on your data science tasks.

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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Learn more about Google Cloud Datalab
Learn more about Microsoft Azure Machine Learning Studio
Find out what your peers are saying about Alteryx, Knime, IBM and others in Data Science Platforms. Updated: June 2019.
347,894 professionals have used our research since 2012.
We monitor all Data Science 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.

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