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 product's standout feature is a robust multi-file network with limited availability."
"MLS allows me to set up data experiments by running through various regression and other machine learning algorithms, with different data cleaning and treatment tools. All of this can be achieved via drag and drop, and a few clicks of the mouse."
"The most valuable feature of this solution is the ability to use all of the cognitive services, prebuilt from Azure."
"The most valuable feature of Microsoft Azure Machine Learning Studio is the ease of use for starting projects. It's simple to connect and view the results. Additionally, the solution works well with other Microsoft solutions, such as Power Automate or SQL Server. It is easy to use and to connect for analytics."
"The solution facilitates our production."
"The solution is integrated with our Microsoft Azure tenant, and we don't have to go anywhere else outside the tenant."
"The graphical nature of the output makes it very easy to create PowerPoint reports as well."
"I like that it's totally easy to use. They have an AutoML solution, and their machine learning model is highly accurate. They also have a feature that can explain the machine learning model. This makes it easy for me to understand that model."
"I like not having to write all solutions from code. Being able to drag and drop controls, enables me to focus on building the best model, without needing to search for syntax errors or extra libraries."
"The most valuable feature is what the product sets out to do, which is extracting information and data."
"Using the GUI, I can have models and algorithms drag and drop nodes."
"The most valuable features are the Binary classification and Auto Model."
"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."
"The best part of RapidMiner is efficiency."
"What I like about RapidMiner is its all-in-one nature, which allows me to prepare, extract, transform, and load data within the same tool."
"The data science, collaboration, and IDN are very, very strong."
"The product must improve its documentation."
"Overall, the icons in the solution could be improved to provide better guidance to users. Additionally, the setup process for the solution could be made easier."
"One area where Azure Machine Learning Studio could improve is its user interface structure."
"The solution cannot connect to private block storage."
"The speed of deployment should be faster, as should testing."
"Stability-wise, you may face certain problems when you fail to refresh the data in the solution."
"They should have a desktop version to work on the platform."
"Operability with R could be improved."
"RapidMiner would be improved with the inclusion of more machine learning algorithms for generating time-series forecasting models."
"I would like to see all users have access to all of the deep learning models, and that they can be used easily."
"It would be helpful to have some tutorials on communicating with Python."
"The biggest problem, not from a platform process, but from an avoidance process, is when you work in a heavily regulated environment, like banking and finance. Whenever you make a decision or there is an output, you need to bill it as an avoidance to the investigator or to the bank audit team. If you made decisions within this machine learning model, you need to explain why you did so. It would better if you could explain your decision in terms of delivery. However, this is an issue with all ML platforms. Many companies are working heavily in this area to help figure out how to make it more explainable to the business team or the regulator."
"The price of this solution should be improved."
"I think that they should make deep learning models easier."
"In terms of the UI and SaaS, the user interface with KNIME is more appealing than RapidMiner."
"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."
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Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 49 reviews while RapidMiner is ranked 7th in Data Science Platforms with 19 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 "Offers good tutorials that make it easy to learn and use, with a powerful feature to compare machine learning algorithms". Microsoft Azure Machine Learning Studio is most compared with Databricks, Google Vertex AI, Azure OpenAI, TensorFlow and Anaconda, whereas RapidMiner is most compared with KNIME, Alteryx, Dataiku Data Science Studio, Tableau and IBM SPSS Modeler. See our Microsoft Azure Machine Learning Studio vs. RapidMiner report.
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