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 drag-and-drop interface of Azure Machine Learning Studio has greatly improved my workflow."
"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."
"I like being able to compare results across different training runs. The hyperparameter tuning function is a valuable feature because it provides the ability to run multiple experiments at the same time and compare results."
"The initial setup is very simple and straightforward."
"I find Microsoft Azure Machine Learning Studio advantageous because it allows integration with Titan Scratch and offers an easy-to-use drag-and-drop menu for developing machine learning models."
"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."
"One of the notable advantages is that it offers both a visual designer, which is user-friendly, and an advanced coding option."
"The product supports open-source tools."
"I've been using a lot of components from the Strategic Extension and Python Extension."
"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 most valuable feature of RapidMiner is that it can read a large number of file formats including CSV, Excel, and in particular, SPSS."
"RapidMiner for Windows is an excellent graphical tool for data science."
"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."
"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 regulatory requirements of the product need improvement."
"The solution's initial setup process is complicated."
"In the future, I would like to see more AI consultation like image and video classification, and improvement in the presentation of data."
"They should have a desktop version to work on the platform."
"The price of the solution has room for improvement."
"It is not easy. It is a complex solution. It takes some time to get exposed to all the concepts. We're trying to have a CI/CD pipeline to deploy a machine learning model using negative actions. It was not easy. The components that we're using might have something to do with this."
"The solution cannot connect to private block storage."
"Microsoft should also include more examples and tutorials for using this product."
"A great product but confusing in some way with regard to the user interface and integration with other tools."
"Improve the online data services."
"RapidMiner isn't cheap. It's a complete solution, but it's costly."
"In terms of the UI and SaaS, the user interface with KNIME is more appealing than RapidMiner."
"If they could include video tutorials, people would find that quite helpful."
"The price of this solution should be improved."
"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."
"It would be helpful to have some tutorials on communicating with Python."
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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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