We performed a comparison between Microsoft Azure Machine Learning Studio and PyTorch 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 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."
"The solution is very fast and simple for a data science solution."
"Split dataset, variety of algorithms, visualizing the data, and drag and drop capability are the features I appreciate most."
"It's good for citizen data scientists, but also, other people can use Python or .NET code."
"One of the notable advantages is that it offers both a visual designer, which is user-friendly, and an advanced coding option."
"Their support is helpful."
"Regarding the technical support for the solution, I find the documentation provided comprehensive and helpful."
"It's easy to use."
"yTorch is gaining credibility in the research space, it's becoming easier to find examples of papers that use PyTorch. This is an advantage for someone who uses PyTorch primarily."
"Its interface is the most valuable. The ability to have an interface to train machine learning models and construct them with the high-level interface, without excess busting and reconstructing the same technical elements, is very useful."
"I like that PyTorch actually follows the pythonic way, and I feel that it's quite easy. It's easy to find compared to others who require us to type a long paragraph of code."
"The framework of the solution is valuable."
"It's been pretty scalable in terms of using multiple GPUs."
"The tool is very user-friendly."
"I would like to see modules to handle Deep Learning frameworks."
"When you use different Microsoft tools, there are different pricing metrics. It doesn't make sense. The pricing metrics are quire difficult to understand and should be either clarified or simplified. It would help us sell the solution to customers."
"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."
"Microsoft Azure Machine Learning Studio worked okay for me, so right now, I don't have any room for improvement in mind for it. What I'd like added to Microsoft Azure Machine Learning Studio in its next version is a categorization for use cases or a template that makes the use cases simple to map out, for example, for healthcare, medical, or finance use cases, etc. This would be very helpful for users of Microsoft Azure Machine Learning Studio, especially for beginners."
"There's room for improvement in terms of binding the integration with Azure DevOps."
"Technical support could improve their turnaround time."
"There is not enough documentation about some methods and parameters. It is sometimes difficult to find information."
"PyTorch could make certain things more obvious. Even though it does make things like defining loss functions and calculating gradients in backward propagation clear, these concepts may confuse beginners. We find that it's kind of problematic. Despite having methods called on loss functions during backward passes, the oral documentation for beginners is quite complex."
"I would like a model to be available. I think Google recently released a new version of EfficientNet. It's a really good classifier, and a PyTorch implementation would be nice."
"The training of the models could be faster."
"On the production side of things, having more frameworks would be helpful."
"I've had issues with stability when I use a lot of data and try out different combinations of modeling techniques."
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Microsoft Azure Machine Learning Studio is ranked 1st in AI Development Platforms with 48 reviews while PyTorch is ranked 11th in AI Development Platforms with 6 reviews. Microsoft Azure Machine Learning Studio is rated 7.6, while PyTorch 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 PyTorch writes "Offers good backward compatible and simple to use". Microsoft Azure Machine Learning Studio is most compared with Databricks, Google Vertex AI, Azure OpenAI, TensorFlow and Google Cloud AI Platform, whereas PyTorch is most compared with OpenVINO, MXNet, Google Cloud AI Platform, Caffe and Google Vertex AI. See our Microsoft Azure Machine Learning Studio vs. PyTorch report.
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