We performed a comparison between IBM Watson Studio and Microsoft Azure Machine Learning Studio 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."It has greatly improved the performance because it is standardized across the company."
"The scalability of IBM Watson Studio is great."
"Stability-wise, it is a great tool."
"Watson Studio is very stable."
"It is a very stable and reliable solution."
"For me, the valuable feature of the solution is the one that I used, which was Jupyter notebooks."
"It stands out for its substantial AI capabilities, offering a broad spectrum of features for crafting solutions that meet specific requirements."
"It is a stable, reliable product."
"The ability to do the templating and be able to transfer it so that I can easily do multiple types of models and data mining is a valuable aspect of this solution. You only have to set up the flows, the templates, and the data once and then you can make modifications and test different segmentations throughout."
"The solution is scalable."
"The solution's most beneficial feature is its integration with Azure."
"In terms of what I found most valuable in Microsoft Azure Machine Learning Studio, I especially love the designer because you can just drag and drop items there and apply the logic that's already available with the designer. I love that I can use the libraries in Microsoft Azure Machine Learning Studio, so I don't have to search for the algorithms and all the relevant libraries because I can see them directly on the designer just by dragging and dropping. Though there's a bit of work during data cleansing, that's normal and can't be avoided. At least it's easy to find the relevant algorithm, apply that algorithm to the data, then get the desired output through Microsoft Azure Machine Learning Studio. I also like the API feature of the solution which is readily available for me to expose the output to any consuming application, so that takes out a lot of headache. Otherwise, I have to have a developer who knows the API, and I have to have an API app, so all that is completely taken care of by the Microsoft Azure Machine Learning Studio designer. With the solution, I can concentrate on how to improve the data quality to get quality recommendations, so this lets me concentrate on my job rather than focusing on the regular development of APIs or the pipelines, in particular, the data pipelines pulling the data from other sources. All the data is taken care of and you can also concentrate on other required auxiliary activities rather than just concentrating on machine learning."
"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 interface is very intuitive."
"The AutoML is helpful when you're starting to explore the problem that you're trying to solve."
"Visualisation, and the possibility of sharing functions are key features."
"Some of the solutions are really good solutions but they can be a little too costly for many."
"I want IBM's technical support team to provide more specific answers to queries."
"Watson Studio would be improved with a clearer path for the deployment of docker images."
"We would like to see it less as one big, massive product, but more based on smaller services that we can then roll out to consumers."
"We would like to see it more web-based with more functionality."
"So a better user interface could be very helpful"
"The solution's interface is very slow at times."
"The decision making in their decision making feature is less good than other options."
"The solution should be more customizable. There should be more algorithms."
"The speed of deployment should be faster, as should testing."
"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."
"The regulatory requirements of the product need improvement."
"Microsoft should also include more examples and tutorials for using this product."
"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."
"It would be great if the solution integrated Microsoft Copilot, its AI helper."
"Using the solution requires some specific learning which can take some time."
More Microsoft Azure Machine Learning Studio Pricing and Cost Advice →
IBM Watson Studio is ranked 10th in Data Science Platforms with 13 reviews while Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 51 reviews. IBM Watson Studio is rated 8.2, while Microsoft Azure Machine Learning Studio is rated 7.6. The top reviewer of IBM Watson Studio writes "A highly robust and well-documented platform that simplifies the complex world of AI". On the other hand, the top reviewer of Microsoft Azure Machine Learning Studio writes "Good support for Azure services in pipelines, but deploying outside of Azure is difficult". IBM Watson Studio is most compared with Databricks, Azure OpenAI, Google Vertex AI, Amazon Comprehend and Anaconda, whereas Microsoft Azure Machine Learning Studio is most compared with Google Vertex AI, Databricks, Azure OpenAI, TensorFlow and IBM SPSS Statistics. See our IBM Watson Studio vs. Microsoft Azure Machine Learning Studio report.
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