Microsoft Corporation

Microsoft Azure Machine Learning

Composite Score

8.7 /10

CX Score

9.0 /10

42 Reviews Write a Review

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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.

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Awards & Recognition

Microsoft Azure Machine Learning won the following awards in the Machine Learning Platforms category

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2024 Data Quadrant Gold Medalist

Latest Award, 2024

5 Top Rated Capabilities

9 Top Rated Features

Latest Award, 2024

2023 Emotional Footprint Champion

2023

Strategy and Innovation
Service Experience
Product Impact

2023

2023 Data Quadrant Gold Medalist

2023

6 Top Rated Capabilities

13 Top Rated Features

2023

Microsoft Azure Machine Learning Ratings

Real user data aggregated to summarize the product performance and customer experience.
Download the entire Product Scorecard to access more information on Microsoft Azure Machine Learning.

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.

89 Likeliness to Recommend

100 Plan to Renew

85 Satisfaction of Cost Relative to Value

1
Since last award

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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?

0% Negative

3% Neutral

97% Positive

Pros

Performance Enhancing
Respectful
Includes Product Enhancements
Reliable

Feature Ratings

Average 85

Model Training

Data Exploration and Visualization

Pre-Packaged AI/ML Services

Data Pre-Processing

Feature Engineering

Model Tuning

Performance and Scalability

Data Labeling

Model Monitoring and Management

Data Ingestion

Explainability

Vendor Capability Ratings

Average 82

Breadth of Features

Ease of Data Integration

Quality of Features

Ease of Implementation

Ease of Customization

Availability and Quality of Training

Business Value Created

Ease of IT Administration

Product Strategy and Rate of Improvement

Usability and Intuitiveness

Vendor Support

Microsoft Azure Machine Learning Reviews

Kailash S.

Role: Information Technology
Industry: Consulting
Involvement: IT Development, Integration, and Administration

Validated Review

Verified Reviewer

Submitted Apr 2024

Empowering Data Innovation: A Review of Microsoft

Likeliness to Recommend

9 /10

What differentiates Microsoft Azure Machine Learning from other similar products?

Microsoft Azure Machine Learning sets itself apart with seamless integration, enterprise-grade security, scalability, advanced analytics, collaboration features, and flexibility.

What do you dislike most about this product?

Some common areas for improvement in Microsoft Azure Machine Learning include pricing complexity, steep learning curve, documentation quality, resource management challenges, and performance optimization.

What recommendations would you give to someone considering this product?

Consider your needs, explore tutorials, start small and scale gradually, leverage the Azure ecosystem, invest in training and support, and monitor costs and performance.

Pros

Performance Enhancing
Effective Service
Fair
Includes Product Enhancements

Urnisha S.

Role: Student Academic
Industry: Engineering
Involvement: End User of Application

Validated Review

Verified Reviewer

Submitted Apr 2024

"Very Efficient" "Outstanding Product"

Likeliness to Recommend

10 /10

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

Validated Review

Verified Reviewer

Submitted Apr 2024

Good functionalities, but the ui need improvement.

Likeliness to Recommend

10 /10

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

Microsoft Azure Machine Learning

What is Microsoft Azure Machine Learning?

Company Details

Need Assistance?

Awards & Recognition

2024 Data Quadrant Gold Medalist

2023 Emotional Footprint Champion

2023 Data Quadrant Gold Medalist

Microsoft Azure Machine Learning Ratings

89 Likeliness to Recommend

100 Plan to Renew

85 Satisfaction of Cost Relative to Value

1 Since last award

Emotional Footprint Overview

+92 Net Emotional Footprint

How much do users love Microsoft Azure Machine Learning?

Pros

Feature Ratings Average rating of all product features, some of which may not be shown below

Model Training Ability to train a model with a range of data sets that you provide.

Data Exploration and Visualization Ability to visually manipulate, interact with, and explore data, and perform basic descriptive statistics and pattern detection.

Pre-Packaged AI/ML Services Pre-trained models and associated resources, e.g., for forecasting, recommendations, image and video analysis, NLP, voice, etc.

Data Pre-Processing Ability to wrangle or pre-process data to ready it for model training.

Feature Engineering Ability to extract and build features from raw data.

Model Tuning 'Ability to fine-tune models based on monitoring feedback within the platform.

Performance and Scalability Systems performance (time) and scalability end-to-end: from data load and processing to model creation and deployment.

Data Labeling Ability to annotate/ label data to create a training data set.

Model Monitoring and Management Ability to monitor model use and performance in production, incl. identifying models for refresh and/or replacement.

Data Ingestion Ability to access data from various sources on-prem and in the cloud and of various type: structured, unstructured, and semi-structured, real-time, etc.

Explainability Ability to explain/ visualize the model.

Vendor Capability Ratings Average rating of all vendor capabilities, some of which may not be shown below

Breadth of Features Users prefer feature rich software that enables them to perform diverse series of tasks. This data expresses user satisfaction with the product's breadth of features.

Ease of Data Integration Use this data to determine whether the product will cause headaches or make data integration easy.

Quality of Features Feature quality is just as important as quantity. Use this data to determine if this product will do what you're purchasing it to do, easily, intuitively, reliably, and effectively.

Ease of Implementation Successfully implementing new software is necessary to realize its full value and promote end user adoption. This data indicates whether or not the product is easy to implement.

Ease of Customization Don't get bogged down in a difficult customization; use this data to make sure you can easily achieve the functionality you need for your particular situation.

Availability and Quality of Training Effective and readily available training enables users to get the most out of the software you've chosen. Use this section to make sure your vendor's training programs and materials measure up.

Business Value Created Software needs to create value for employees, customers, partners, and, ultimately, shareholders. This data expresses user satisfaction - or lack thereof - with the product's business value.

Ease of IT Administration This data indicates whether IT personnel will be able to resolve issues and perform configurations efficiently and effectively.

Product Strategy and Rate of Improvement Vendors who don't stay on top of emerging needs and trends won't enable you to meet your business goals. Use this data to separate innovators from imposters.

Usability and Intuitiveness End user learning curves cost the organization money. Pay attention to your end users' technical ability to determine how important UX is in your purchase.

Vendor Support The importance of vendor support will vary for each organization depending on internal capabilities, but there will always be issues that only the vendor can resolve.

Microsoft Azure Machine Learning Reviews

Kailash S.

Empowering Data Innovation: A Review of Microsoft

Likeliness to Recommend

Pros

Urnisha S.

"Very Efficient" "Outstanding Product"

Likeliness to Recommend

Pros

Bir B.

Good functionalities, but the ui need improvement.

Likeliness to Recommend

Pros

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Feature Ratings

Model Training

Data Exploration and Visualization

Pre-Packaged AI/ML Services

Data Pre-Processing

Feature Engineering

Model Tuning

Performance and Scalability

Data Labeling

Model Monitoring and Management

Data Ingestion

Explainability

Vendor Capability Ratings

Breadth of Features

Ease of Data Integration

Quality of Features

Ease of Implementation

Ease of Customization

Availability and Quality of Training

Business Value Created

Ease of IT Administration

Product Strategy and Rate of Improvement

Usability and Intuitiveness

Vendor Support