We performed a comparison between Hugging Face 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."My preferred aspects are natural language processing and question-answering."
"What I find the most valuable about Hugging Face is that I can check all the models on it and see which ones have the best performance without using another platform."
"The solution is scalable."
"It's good for citizen data scientists, but also, other people can use Python or .NET code."
"The initial setup is very simple and straightforward."
"The solution is integrated with our Microsoft Azure tenant, and we don't have to go anywhere else outside the tenant."
"The AutoML is helpful when you're starting to explore the problem that you're trying to solve."
"The most valuable feature is data normalization."
"Anyone who isn't a programmer his whole life can adopt it. All he needs is statistics and data analysis skills."
"Regarding the technical support for the solution, I find the documentation provided comprehensive and helpful."
"The area that needs improvement would be the organization of the materials. It could be clearer and more systematic. It would be good if the layout was clear and we could search the models easily."
"Implementing a cloud system to showcase historical data would be beneficial."
"As for the areas for improvement in Microsoft Azure Machine Learning Studio, I've provided feedback to Microsoft. My company is a Gold Partner of Microsoft, so I provided my feedback in another forum. Right now, it is the number of algorithms available in the designer that has to be improved, though I'm sure Microsoft does it regularly. When you take a use case approach, Microsoft has done that in a lot of places, but not on the Microsoft Azure Machine Learning Studio designer. When I say use case basis, I meant recommending a product or recommending similar products, so if Microsoft can list out use cases and give me a template, it will save me a lot of time and a lot of work because I don't have to scratch my head on which algorithm is better, and I can go with what's recommended by Microsoft. I'm sure that isn't a big task for the Microsoft team who must have seen thousands of use cases already, so out of that experience if the team can come up with a standard template, I'm sure it'll help a lot of organizations cut down on the development time, as well as going with the best industry-standard algorithms rather than experimenting with mine. What I'd like to see in the next version of Microsoft Azure Machine Learning Studio, apart from the use case template, is the improvement of the availability of libraries. Microsoft should also upgrade the Python versions because the old version of Python is still supported and it takes time for Microsoft to upgrade the support for Python. The pace of upgrading Python versions of Microsoft Azure Machine Learning Studio and making those libraries available should be sped up or increased."
"The speed of deployment should be faster, as should testing."
"Microsoft should also include more examples and tutorials for using this product."
"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 product must improve its documentation."
"I personally would prefer if data could be tunneled to my model through a SAP ERP system, and have features of Excel, such as Pivot Tables, integrated."
"There should be data access security, a role level security. Right now, they don't offer this."
"I think they should improve two things. They should make their user interface more user-friendly. Integration could also be better. Because Microsoft Machine Learning is a Microsoft product, it's fully integrated with Microsoft Azure but not fully supported for other platforms like IBM or AWS or something else."
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Hugging Face is ranked 8th in AI Development Platforms with 3 reviews while Microsoft Azure Machine Learning Studio is ranked 1st in AI Development Platforms with 49 reviews. Hugging Face is rated 9.0, while Microsoft Azure Machine Learning Studio is rated 7.6. The top reviewer of Hugging Face writes "A comprehensive natural language processing ecosystem offering a diverse range of pre-trained models and a collaborative platform". 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". Hugging Face is most compared with Google Vertex AI, Azure OpenAI, Replicate, Google Cloud AI Platform and DataRobot, whereas Microsoft Azure Machine Learning Studio is most compared with Databricks, Google Vertex AI, Azure OpenAI, TensorFlow and Google Cloud AI Platform. See our Hugging Face vs. Microsoft Azure Machine Learning Studio report.
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