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."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."
"My preferred aspects are natural language processing and question-answering."
"The solution's most beneficial feature is its integration with Azure."
"The most valuable feature is the knowledge bank, which allows us to ask questions and the AI will automatically pull the pre-prescribed responses."
"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."
"Scalability, in terms of running experiments concurrently is good. At max, I was able to run three different experiments concurrently."
"The visualizations are great. It makes it very easy to understand which model is working and why."
"The solution is scalable."
"The product supports open-source tools."
"The most valuable feature of Microsoft Azure Machine Learning Studio is the ease of use for starting projects. It's simple to connect and view the results. Additionally, the solution works well with other Microsoft solutions, such as Power Automate or SQL Server. It is easy to use and to connect for analytics."
"Implementing a cloud system to showcase historical data would be beneficial."
"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."
"The AutoML feature is very basic and they should improve it by using a more robust algorithm."
"Using the solution requires some specific learning which can take some time."
"Enable creating ensemble models easier, adding more machine learning algorithms."
"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."
"There should be data access security, a role level security. Right now, they don't offer this."
"Technical support could improve their turnaround time."
"The data processor can pose a bit of a challenge, but the real complexity is determined by the skill of the implementation team."
"I think it should be made cheaper for certain people…It may appear costlier for those who don't consider time important."
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Hugging Face is ranked 7th in AI Development Platforms with 3 reviews while Microsoft Azure Machine Learning Studio is ranked 1st in AI Development Platforms with 53 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, Replicate, Azure OpenAI, Google Cloud AI Platform and DataRobot, whereas Microsoft Azure Machine Learning Studio is most compared with Google Vertex AI, Databricks, Azure OpenAI, TensorFlow and Google Cloud AI Platform. See our Hugging Face vs. Microsoft Azure Machine Learning Studio report.
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