We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
"The most valuable feature of this solution is the ability to use all of the cognitive services, prebuilt from Azure."
"The most valuable feature is data normalization."
"The UI is very user-friendly and that AI is easy to use."
"The solution is very fast and simple for a data science solution."
"Anyone who isn't a programmer his whole life can adopt it. All he needs is statistics and data analysis skills."
"The most valuable feature is the knowledge bank, which allows us to ask questions and the AI will automatically pull the pre-prescribed responses."
"The AutoML is helpful when you're starting to explore the problem that you're trying to solve."
"The interface is very intuitive."
"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."
"If you want to be able to deploy your tools outside of Microsoft Azure, this is not the best choice."
"The data cleaning functionality is something that could be better and needs to be improved."
"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 should be more customizable. There should be more algorithms."
"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."
"Integration with social media would be a valuable enhancement."
"The AutoML feature is very basic and they should improve it by using a more robust algorithm."
"The data preparation capabilities need to be improved."
"There is not enough documentation about some methods and parameters. It is sometimes difficult to find information."
"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."
"When we got our first models and were ready for the user acceptance testing, our licensing fees were between €2,500 ($2,750 USD) and €3,000 ($3,300 USD) monthly."
"From a developer's perspective, I find the price of this solution high."
"The licensing cost is very cheap. It's less than $50 a month."
"It is free."
"PyTorch is an open-source solution."
Azure Machine Learning is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions.
It has everything you need to create complete predictive analytics solutions in the cloud, from a large algorithm library, to a studio for building models, to an easy way to deploy your model as a web service. Quickly create, test, operationalize, and manage predictive models.
We've built this course as an introduction to deep learning. Deep learning is a field of machine learning utilizing massive neural networks, massive datasets, and accelerated computing on GPUs. Many of the advancements we've seen in AI recently are due to the power of deep learning. This revolution is impacting a wide range of industries already with applications such as personal voice assistants, medical imaging, automated vehicles, video game AI, and more.
In this course, we'll be covering the concepts behind deep learning and how to build deep learning models using PyTorch. We've included a lot of hands-on exercises so by the end of the course, you'll be defining and training your own state-of-the-art deep learning models.
Microsoft Azure Machine Learning Studio is ranked 1st in AI Development Platforms with 14 reviews while PyTorch is ranked 4th in AI Development Platforms with 2 reviews. Microsoft Azure Machine Learning Studio is rated 7.6, while PyTorch is rated 9.0. 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 "A highly user-friendly open-source machine learning library". Microsoft Azure Machine Learning Studio is most compared with Databricks, IBM Watson Studio, Alteryx, Dataiku Data Science Studio and Amazon SageMaker, whereas PyTorch is most compared with OpenVINO. See our Microsoft Azure Machine Learning Studio vs. PyTorch report.
See our list of best AI Development Platforms vendors.
We monitor all AI Development Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.