We performed a comparison between Microsoft Azure Machine Learning Studio and RapidMiner based on real PeerSpot user reviews.
Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."Visualisation, and the possibility of sharing functions are key features."
"It's a great option if you are fairly new and don't want to write too much code."
"The graphical nature of the output makes it very easy to create PowerPoint reports as well."
"The solution is scalable."
"The solution is very easy to use, so far as our data scientists are concerned."
"The solution's most beneficial feature is its integration with Azure."
"What I like best about Microsoft Azure Machine Learning Studio is that it's a straightforward tool and it's easy to use. Another valuable feature of the tool is AutoML which lets you get better metrics to train the model right and with good accuracy. The AutoML feature allows you to simply put in your data, and it'll pre-process and create a more accurate model for you. You don't have to do anything because AutoML in Microsoft Azure Machine Learning Studio will take care of it."
"It is a scalable solution…It is a pretty stable solution…The solution's initial setup process was pretty straightforward."
"Using the GUI, I can have models and algorithms drag and drop nodes."
"The solution is stable."
"The most valuable feature is what the product sets out to do, which is extracting information and data."
"The most valuable feature of RapidMiner is that it can read a large number of file formats including CSV, Excel, and in particular, SPSS."
"The documentation for this solution is very good, where each operator is explained with how to use it."
"The most valuable feature of RapidMiner is that it is code free. It is similar to playing with Lego pieces and executing after you are finished to see the results. Additionally, it is easy to use and has interesting utilities when preparing the data. It has a utility to automatically launch a series of models and show the comparisons. When finished with the comparisons you can select the best one, and deploy it automatically."
"Scalability is not really a concern with RapidMiner. It scales very well and can be used in global implementations."
"RapidMiner is a no-code machine learning tool. I can install it on my local machine and work with smaller datasets. It can also connect to databases, allowing me to build models directly on the data stored there. RapidMiner offers a wider range of operators than other tools like Dataiku, making it a better option for my needs."
"While ML Studio does give you the ability to run a lot of transformations, it struggles when the transformations are a bit more complex, when your entire process is transformation-heavy."
"Stability-wise, you may face certain problems when you fail to refresh the data in the solution."
"Microsoft Azure Machine Learning Studio worked okay for me, so right now, I don't have any room for improvement in mind for it. What I'd like added to Microsoft Azure Machine Learning Studio in its next version is a categorization for use cases or a template that makes the use cases simple to map out, for example, for healthcare, medical, or finance use cases, etc. This would be very helpful for users of Microsoft Azure Machine Learning Studio, especially for beginners."
"Operability with R could be improved."
"There should be data access security, a role level security. Right now, they don't offer this."
"We can create a label job, but we still have to use the Azure Machine Learning REST APIs, which are not yet supported in the Python SDK version 2."
"The regulatory requirements of the product need improvement."
"In terms of improvement, I'd like to have more ability to construct and understand the detailed impact of the variables on the model. Their algorithms are very powerful and they explain overall the net contribution of each of the variables to the solution. In terms of being able to say to people "If you did this, you'll get this much more improvement" it wasn't great."
"If they could include video tutorials, people would find that quite helpful."
"A great product but confusing in some way with regard to the user interface and integration with other tools."
"RapidMiner isn't cheap. It's a complete solution, but it's costly."
"I would like to see more integration capabilities."
"The price of this solution should be improved."
"The visual interface could use something like the-drag-and-drop features which other products already support. Some additional features can make RapidMiner a better tool and maybe more competitive."
"I would like to see all users have access to all of the deep learning models, and that they can be used easily."
"RapidMiner can improve deep learning by enhancing the features."
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Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 53 reviews while RapidMiner is ranked 6th in Data Science Platforms with 20 reviews. Microsoft Azure Machine Learning Studio is rated 7.6, while RapidMiner is rated 8.6. The top reviewer of Microsoft Azure Machine Learning Studio writes "Good support for Azure services in pipelines, but deploying outside of Azure is difficult". On the other hand, the top reviewer of RapidMiner writes "A no-code tool that helps to build machine learning models ". Microsoft Azure Machine Learning Studio is most compared with Google Vertex AI, Databricks, Azure OpenAI, TensorFlow and Anaconda, whereas RapidMiner is most compared with KNIME, Alteryx, Dataiku, Tableau and IBM SPSS Modeler. See our Microsoft Azure Machine Learning Studio vs. RapidMiner report.
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