We compared Microsoft Azure Machine Learning Studio and Azure OpenAI based on our user's reviews in several parameters.
Microsoft Azure Machine Learning Studio offers a user-friendly interface, excellent support, and flexible pricing options. Users have highlighted the need for better documentation and collaboration features. Azure OpenAI, on the other hand, focuses on seamless integration, scalable resources, and robust machine learning capabilities. Users appreciate its affordable pricing, extensive support, and positive ROI. Areas for improvement include specific functions and enhancements.
Features: Microsoft Azure Machine Learning Studio offers a user-friendly interface, a wide range of tools and algorithms, seamless integration with other Azure services, reliable and scalable performance, and excellent support and documentation. In comparison, Azure OpenAI focuses on seamless integration with other Azure services, flexibility in resource scaling, robust machine learning capabilities, and extensive documentation and support.
Pricing and ROI: Azure Machine Learning Studio offers flexible pricing options with reasonable setup costs, according to user feedback. On the other hand, Azure OpenAI is positively regarded for its affordable pricing and minimal setup cost. Users find it cost-efficient and note the smooth setup process. Azure OpenAI also provides adaptable licensing options., The ROI of Microsoft Azure Machine Learning Studio includes cost savings, improved efficiency, and reliable predictions. Azure OpenAI offers increased efficiency, cost reduction, and valuable insights for better decision-making.
Room for Improvement: Microsoft Azure Machine Learning Studio: Users have identified areas for improvement, including enhancing the user interface, better documentation and guidance, improved collaboration features, and seamless integration with other tools. Azure OpenAI: Users have provided feedback on enhancing Azure OpenAI, including concerns regarding certain functions and suggested improvements.
Deployment and customer support: The user reviews for Microsoft Azure Machine Learning Studio indicate some variation in the durations for deployment, setup, and implementation phases, suggesting that these processes may occur at different times. In contrast, the reviews for Azure OpenAI suggest that deployment and setup are considered to be the same period and should not be evaluated separately., Microsoft Azure Machine Learning Studio's customer service is praised for being prompt, knowledgeable, and efficient. On the other hand, Azure OpenAI's customer service is regarded as highly appreciated, efficient, and reliable, ensuring a smooth user experience.
The summary above is based on 35 interviews we conducted recently with Microsoft Azure Machine Learning Studio and Azure OpenAI users. To access the review's full transcripts, download our report.
"Azure OpenAI is very easy to use instead of AWS services."
"The product's initial setup phase was pretty easy."
"We have many use cases for the solution, such as digitalizing records, a chatbot looking at records, and being able to use generative AI on them."
"The most valuable feature of Azure OpenAI stems from the GPT-3.5 models it provides to its users."
"Generative AI or GenAI seems to be the best part of the solution."
"The product saves a lot of time."
"The solution has a very drag-and-drop environment. Instead of coding something from scratch or understanding any concept in extensive depth before deployment, this is good. Plus, they have an auto dataset, which means you can choose any dataset they have instead of providing your own. So that's also pretty nice."
"We can use the solution to implement our tasks and models quickly."
"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 most valuable feature is data normalization."
"The UI is very user-friendly and that AI is easy to use."
"The most valuable feature of the solution is the availability of ChatGPT in the solution."
"The graphical nature of the output makes it very easy to create PowerPoint reports as well."
"What I like best about Microsoft Azure Machine Learning Studio is that it's a straightforward tool and it's easy to use. Another valuable feature of the tool is AutoML which lets you get better metrics to train the model right and with good accuracy. The AutoML feature allows you to simply put in your data, and it'll pre-process and create a more accurate model for you. You don't have to do anything because AutoML in Microsoft Azure Machine Learning Studio will take care of it."
"It's easy to use."
"I like that it's totally easy to use. They have an AutoML solution, and their machine learning model is highly accurate. They also have a feature that can explain the machine learning model. This makes it easy for me to understand that model."
"The solution needs to accommodate smaller companies."
"The product must improve its dashboards."
"There are certain shortcomings with the product's scalability and support team where improvements are required."
"Deployment was slightly complex for me to understand."
"There is room for improvement in their support services."
"The product features themselves are fine. However, with Microsoft scaling the service so much, the support structure needs to keep pace. When solving complex issues, the process of interacting with Microsoft can be quite time-consuming."
"Since we don't train the model on our data, it's a struggle to ensure OpenAI answers questions exclusively from our data. During user testing, we found ways to make the system provide answers from outside sources."
"We are awaiting the new updates like multi-model capabilities."
"There's room for improvement in terms of binding the integration with Azure DevOps."
"The solution should be more customizable. There should be more algorithms."
"They should have a desktop version to work on the platform."
"The interface is a bit overloaded."
"The data processor can pose a bit of a challenge, but the real complexity is determined by the skill of the implementation team."
"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."
"It could use to add some more features in data transformation, time series and the text analytics section."
"Overall, the icons in the solution could be improved to provide better guidance to users. Additionally, the setup process for the solution could be made easier."
More Microsoft Azure Machine Learning Studio Pricing and Cost Advice →
Azure OpenAI is ranked 2nd in AI Development Platforms with 17 reviews while Microsoft Azure Machine Learning Studio is ranked 1st in AI Development Platforms with 49 reviews. Azure OpenAI is rated 8.0, while Microsoft Azure Machine Learning Studio is rated 7.6. The top reviewer of Azure OpenAI writes "Created a chatbot powered by OpenAI to answer HR, travel, and expense-related questions". 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". Azure OpenAI is most compared with Google Vertex AI, Amazon SageMaker, Hugging Face, Google Cloud AI Platform and IBM Watson Studio, whereas Microsoft Azure Machine Learning Studio is most compared with Databricks, Google Vertex AI, TensorFlow, Google Cloud AI Platform and Dataiku Data Science Studio. See our Azure OpenAI vs. Microsoft Azure Machine Learning Studio report.
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