In terms of what I found most valuable in Microsoft Azure Machine Learning Studio, I especially love the designer because you can just drag and drop items there and apply the logic that's already available with the designer. I love that I can use the libraries in Microsoft Azure Machine Learning Studio, so I don't have to search for the algorithms and all the relevant libraries because I can see them directly on the designer just by dragging and dropping. Though there's a bit of work during data cleansing, that's normal and can't be avoided. At least it's easy to find the relevant algorithm, apply that algorithm to the data, then get the desired output through Microsoft Azure Machine Learning Studio.
I also like the API feature of the solution which is readily available for me to expose the output to any consuming application, so that takes out a lot of headache. Otherwise, I have to have a developer who knows the API, and I have to have an API app, so all that is completely taken care of by the Microsoft Azure Machine Learning Studio designer. With the solution, I can concentrate on how to improve the data quality to get quality recommendations, so this lets me concentrate on my job rather than focusing on the regular development of APIs or the pipelines, in particular, the data pipelines pulling the data from other sources. All the data is taken care of and you can also concentrate on other required auxiliary activities rather than just concentrating on machine learning.
Microsoft Azure Machine Learning Studio is the #1 ranked solution in top AI Development Platforms and #3 ranked solution in top Data Science Platforms. PeerSpot users give Microsoft Azure Machine Learning Studio an average rating of 7.6 out of 10. Microsoft Azure Machine Learning Studio is most commonly compared to Databricks: Microsoft Azure Machine Learning Studio vs Databricks. Microsoft Azure Machine Learning Studio is popular among the large enterprise segment, accounting for 71% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a computer software company, accounting for 15% of all views.
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Microsoft Azure Machine Learning Studio Buyer's Guide
Download the Microsoft Azure Machine Learning Studio Buyer's Guide including reviews and more. Updated: November 2022
What is Microsoft Azure Machine Learning Studio?
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.
Microsoft Azure Machine Learning Will Help You:
- Rapidly build and train models
- Operationalize at scale
- Deliver responsible solutions
- Innovate on a more secure hybrid platform
With Microsoft Azure Machine Learning You Can:
- Prepare data: Microsoft Azure Machine Learning Studio offers data labeling, data preparation, and datasets.
- Build and train models: Includes notebooks, Visual Studio Code and Github, Automated ML, Compute instance, a drag-and-drop designer, open-source libraries and frameworks, customizable dashboards, and experiments
- Validate and deploy: Manage endpoints, automate machine learning workflows (pipeline CI/CD), optimize models, access pre-built container images, share and track models and data, train and deploy models across multi-cloud and on-premises.
- Manage and monitor: Track, log, and analyze data, models, and resources; Detect drift and maintain model accuracy; Trace ML artifacts for compliance; Apply quota management and automatic shutdown; Leverage built-in and custom policies for compliance management; Utilize continuous monitoring with Azure Security Center.
Microsoft Azure Machine Learning Features:
- Easy & flexible building interface: Execute your machine learning development through the Microsoft Azure Machine Learning Studio using drag-and-drop components that minimize the code development and straightforward configuration of properties. By being so flexible, the solution also helps build, test ,and generate advanced analytics based on the data.
- Wide range of supported algorithms: Configuration is simple and easy because Microsoft Azure ML offers readily available well-known algorithms. There is also no limit in importing training data, and the solution enables you to fine-tune your data easily, saving money and time and helping you generate more revenue.
- Easy implementation of web services: Simply drag and drop your data sets and algorithms, and link them together to implement web services. It only requires one click to create and publish the web service, which can be used from any device by passing valid credentials.
- Great documentation: Microsoft Azure provides full stacks of documentation, such as tutorials, quick starts, references, and many other resources that help you understand how to easily build, manage, deploy, and access machine learning solutions effectively.
Microsoft Azure Machine Learning Benefits:
- It is fully integrated with Python and R SDKs.
- It has an updated drag-and-drop interface, generally known as Azure Machine Learning Designer.
- It supports MLPipelines, where you can build flexible and modular pipelines to automate workflows.
- It supports multiple model formats depending upon the job type.
- It has automated model training and hyperparameter tuning with code-first and no-code options.
- It supports data labeling projects.
Reviews from Real Users:
"The ability to do the templating and be able to transfer it so that I can easily do multiple types of models and data mining is a valuable aspect of this solution. You only have to set up the flows, the templates, and the data once and then you can make modifications and test different segmentations throughout.” - Channing S.l, Owner at Channing Stowell Associates
"The most valuable feature is the knowledge bank, which allows us to ask questions and the AI will automatically pull the pre-prescribed responses.” - Chris P., Tech Lead at a tech services company
"The UI is very user-friendly and the AI is easy to use.” - Mikayil B., CRM Consultant at a computer software company
"The solution is very fast and simple for a data science solution.” - Omar A., Big Data & Cloud Manager at a tech services company
Microsoft Azure Machine Learning Studio was previously known as Azure Machine Learning, MS Azure Machine Learning Studio.
Microsoft Azure Machine Learning Studio Customers
Walgreens Boots Alliance, Schneider Electric, BP
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Microsoft Azure Machine Learning Studio
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