Microsoft Azure Machine Learning
What is Microsoft Azure Machine Learning?
Machine Learning Studio is a powerfully simple browser-based, visual drag-and-drop authoring environment where no coding is necessary. Go from idea to deployment in a matter of clicks. Microsoft Azure Machine Learning Studio is a collaborative, drag-and-drop tool you can use to build, test, and deploy predictive analytics solutions on your data. Machine Learning Studio publishes models as web services that can easily be consumed by custom apps or BI tools such as Excel.
Company Details
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Real user data aggregated to summarize the product performance and customer experience.
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Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.
88 Likeliness to Recommend
1
Since last award
95 Plan to Renew
83 Satisfaction of Cost Relative to Value
Emotional Footprint Overview
Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.
+92 Net Emotional Footprint
The emotional sentiment held by end users of the software based on their experience with the vendor. Responses are captured on an eight-point scale.
How much do users love Microsoft Azure Machine Learning?
Pros
- Performance Enhancing
- Helps Innovate
- Reliable
- Includes Product Enhancements
How to read the Emotional Footprint
The Net Emotional Footprint measures high-level user sentiment towards particular product offerings. It aggregates emotional response ratings for various dimensions of the vendor-client relationship and product effectiveness, creating a powerful indicator of overall user feeling toward the vendor and product.
While purchasing decisions shouldn't be based on emotion, it's valuable to know what kind of emotional response the vendor you're considering elicits from their users.
Footprint
Negative
Neutral
Positive
Feature Ratings
Pre-Packaged AI/ML Services
Model Training
Data Labeling
Model Tuning
Data Exploration and Visualization
Algorithm Diversity
Feature Engineering
Data Pre-Processing
Model Monitoring and Management
Algorithm Recommendation
Ensembling
Vendor Capability Ratings
Ease of Data Integration
Ease of Customization
Quality of Features
Product Strategy and Rate of Improvement
Availability and Quality of Training
Breadth of Features
Ease of Implementation
Ease of IT Administration
Usability and Intuitiveness
Vendor Support
Business Value Created
Microsoft Azure Machine Learning Reviews
Urnisha S.
- Role: Student Academic
- Industry: Engineering
- Involvement: End User of Application
Submitted Apr 2024
"Very Efficient" "Outstanding Product"
Likeliness to Recommend
What differentiates Microsoft Azure Machine Learning from other similar products?
The exceptional scalability, dependability, and flexibility of Microsoft Azure Machine Learning are made possible by its smooth connection with the larger Azure ecosystem. The full machine learning lifecycle—which includes data preparation, model training, deployment, and monitoring—is supported by its extensive toolkit. Moreover, its capacity to accommodate various infrastructure requirements is guaranteed by its support for multi-cloud and hybrid deployments. Overall, what distinguishes Azure ML from other similar products is its combination of strong features, scalability, and ecosystem integration.
What is your favorite aspect of this product?
The best thing about Microsoft Azure Machine Learning, in my opinion, is how well it integrates with the larger Azure ecosystem while providing a full range of tools and services for machine learning workflows from start to finish. For optimal effectiveness and productivity, users may take advantage of this integration's scalable architecture, varied data sources, and powerful AI capabilities all within a single, integrated environment.
What do you dislike most about this product?
Azure works well according to my requirements, and I am quite benefiting from this software, but I just hope that it is a little bit less costly.
What recommendations would you give to someone considering this product?
For someone considering Microsoft Azure Machine Learning, I strongly advise carefully evaluating their unique requirements and goals. Analyze Azure ML's capabilities in relation to their needs, taking into account aspects like scalability, user-friendliness, system integration, and compatibility with the programming languages and frameworks of their choice. Additionally, learn about the platform and make the most of its potential for their machine learning projects by utilizing the tools that are readily available, such as tutorials, documentation, and customer support.
Pros
- Helps Innovate
- Continually Improving Product
- Reliable
- Performance Enhancing
Bir B.
- Role: Industry Specific Role
- Industry: Technology
- Involvement: IT Development, Integration, and Administration
Submitted Apr 2024
Good functionalities, but the ui need improvement.
Likeliness to Recommend
What differentiates Microsoft Azure Machine Learning from other similar products?
Its easy to use functionalities and continuously updating software.
What is your favorite aspect of this product?
functionalities are easy to use, adaptive and ensembling is also easy.
What do you dislike most about this product?
Nothing as of now.
What recommendations would you give to someone considering this product?
Start with documentation for ease of use, learning might be steep, but after that, its kids play.
Pros
- Reliable
- Performance Enhancing
- Enables Productivity
- Trustworthy
Ketan S.
- Role: Information Technology
- Industry: Engineering
- Involvement: IT Leader or Manager
Submitted Mar 2024
easy & quick to setup end-to-end AI/ML solutions
Likeliness to Recommend
What differentiates Microsoft Azure Machine Learning from other similar products?
1. Provide variety of services to successfully build any AI/ML solution easily for e.g Blob storage, visualization tools, BI tools, Model training & testing tools. 2. Additionally, we can share and collaborate with team on Azure itself which is really helpful when you are working in remote environment
What is your favorite aspect of this product?
I loved working the data labelling service. Web based UI makes it very easy to annotate data from anywhere and collaborate with the team. Also, various annotation shapes are available which makes it suitable for any business solution.
What do you dislike most about this product?
They don't have any AI recommendation services yet, which will make life of AI developer very easy.
What recommendations would you give to someone considering this product?
If you want quickly set up and make your AI environment up and running you should definitely give it a try. There will be a learning curve so as to understand the services , but once you are comfortable it will be worth it.
Pros
- Efficient Service
- Transparent
- Appreciates Incumbent Status
- Security Protects
Cons
- Slower Product Innovation
- Commodity Features
- Vendor Friendly Policies
