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."The visualizations are great. It makes it very easy to understand which model is working and why."
"When you import the dataset you can see the data distribution easily with graphics and statistical measures."
"The solution is very easy to use, so far as our data scientists are concerned."
"Anyone who isn't a programmer his whole life can adopt it. All he needs is statistics and data analysis skills."
"Its ability to publish a predictive model as a web based solution and integrate R and python codes are amazing."
"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."
"The product is well organized. The thing is how we will get the models to work within our code. We have some suggestions there, but we want to gain more experience and be ready to answer that because we are currently working on this and don't have all the answers yet. The tool is well organized. What I am very happy about is the ease of deploying new resources. You can easily create your pipeline within minutes."
"It is a scalable solution…It is a pretty stable solution…The solution's initial setup process was pretty straightforward."
"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."
"The best part of RapidMiner is efficiency."
"Scalability is not really a concern with RapidMiner. It scales very well and can be used in global implementations."
"RapidMiner for Windows is an excellent graphical tool for data science."
"Using the GUI, I can have models and algorithms drag and drop nodes."
"The GUI capabilities of the solution are excellent. Their Auto ML model provides for even non-coder data scientists to deploy a model."
"We value the collaboration and governance features because it's a comprehensive platform that covers everything from data extraction to modeling operations in the ML language. RapidMiner is competitive in the ML space."
"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."
"Operability with R could be improved."
"I have found Databricks is a better solution because it has a lot of different cluster choices and better integration with MLflow, which is much easier to handle in a machine learning system."
"This solution could be improved if they could integrate the data pipeline scheduling part for their interface."
"The speed of deployment should be faster, as should testing."
"If you want to be able to deploy your tools outside of Microsoft Azure, this is not the best choice."
"The solution cannot connect to private block storage."
"The data processor can pose a bit of a challenge, but the real complexity is determined by the skill of the implementation team."
"Using the solution requires some specific learning which can take some time."
"The price of this solution should be improved."
"RapidMiner can improve deep learning by enhancing the features."
"A great product but confusing in some way with regard to the user interface and integration with other tools."
"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."
"Many things in the interface look nice, but they aren't of much use to the operator. It already has lots of variables in there."
"Improve the online data services."
"The server product has been getting updated and continues to be better each release. When I started using RapidMiner, it was solid but not easy to set up and upgrade."
"I would appreciate improvements in automation and customization options to further streamline processes."
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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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