We performed a comparison between IBM Watson Machine Learning and Microsoft Azure Machine Learning Studio based on real PeerSpot user reviews.
Find out in this report how the two AI Development Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."It is has a lot of good features and we find the image classification very useful."
"The most valuable aspect of the solution's the cost and human labor savings."
"Scalability-wise, I rate the solution ten out of ten."
"The solution is very valuable to our organization due to the fact that we can work on it as a workflow."
"It has improved self-service and customer satisfaction."
"I was particularly interested in trying the AutoML feature to see how it handles data and proposes new models. The variety of models it provides is impressive."
"It is very easy to test different kinds of machine-learning algorithms with different parameters. You choose the algorithm, drag and drop to the workspace, and plug the dataset into this component."
"Azure's AutoML feature is probably better than the competition."
"It has helped in reducing the time involved for coding using R and/or Python."
"The learning curve is very low. Operationalizing the model is also very easy within the Azure ecosystem."
"Azure Machine Learning Studio's most valuable features are the package from Azure AutoML. It is quite powerful compared to the building of ML in Databricks or other AutoMLs from other companies, such as Google and Amazon."
"The product's standout feature is a robust multi-file network with limited availability."
"The most valuable feature is data normalization."
"It is a scalable solution…It is a pretty stable solution…The solution's initial setup process was pretty straightforward."
"Honestly, I haven't seen any comparative report that has run the same data through two different artificial intelligence or machine learning capabilities to get something out of it. I would love to see that."
"In future releases, I would like to see a more flexible environment."
"The supporting language is limited."
"They should add more GPU processing power to improve performance, especially when dealing with large amounts of data."
"Scaling is limited in some use cases. They need to make it easier to expand in all aspects."
"If I consider how we want to use it in our organization, certain areas of improvement can be addressed. For instance, we want to use it with Generative AI, not like ChatGPT, but in a way intended for industrial use."
"A problem that I encountered was that I had to pay for the model that I wanted to deploy and use on Azure Machine Learning, but there wasn't any option that that model can be used in the designer."
"If you want to be able to deploy your tools outside of Microsoft Azure, this is not the best choice."
"Microsoft Azure Machine Learning Studio could improve by adding pixel or image analysis. This is a priority for me."
"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."
"In the future, I would like to see more AI consultation like image and video classification, and improvement in the presentation of data."
"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."
"The solution cannot connect to private block storage."
"The interface is a bit overloaded."
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IBM Watson Machine Learning is ranked 9th in AI Development Platforms with 6 reviews while Microsoft Azure Machine Learning Studio is ranked 1st in AI Development Platforms with 49 reviews. IBM Watson Machine Learning is rated 8.0, while Microsoft Azure Machine Learning Studio is rated 7.6. The top reviewer of IBM Watson Machine Learning writes "A highly efficient solution that delivers the desired results to its users". 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 Machine Learning is most compared with Google Cloud AI Platform, Azure OpenAI and TensorFlow, whereas Microsoft Azure Machine Learning Studio is most compared with Databricks, Google Vertex AI, Azure OpenAI, TensorFlow and Google Cloud AI Platform. See our IBM Watson Machine Learning vs. Microsoft Azure Machine Learning Studio report.
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