Microsoft Corporation

Microsoft Azure Machine Learning

Composite Score

8.8 /10

CX Score

9.1 /10

51 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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2025 Data Quadrant Champion

Latest Award, 2025

6 Top Rated Capabilities

6 Top Rated Features

Latest Award, 2025

2024 Emotional Footprint Champion

2024

Product Impact

2024

2024 Data Quadrant Champion

2024

5 Top Rated Capabilities

9 Top Rated Features

2024

2023 Emotional Footprint Champion

2023

Strategy and Innovation
Service Experience
Product Impact

2023

2023 Data Quadrant Champion

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.

90 Likeliness to Recommend

1
Since last award

100 Plan to Renew

86 Satisfaction of Cost Relative to Value

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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.

+93 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?

2% Negative

2% Neutral

96% Positive

Pros

Performance Enhancing
Respectful
Reliable
Enables Productivity

Feature Ratings

Average 85

Data Exploration and Visualization

Model Training

Data Pre-Processing

Model Tuning

Feature Engineering

Pre-Packaged AI/ML Services

Data Labeling

Model Monitoring and Management

Data Ingestion

Ensembling

Explainability

Vendor Capability Ratings

Average 83

Quality of Features

Ease of Customization

Breadth of Features

Ease of Implementation

Ease of Data Integration

Ease of IT Administration

Availability and Quality of Training

Usability and Intuitiveness

Business Value Created

Product Strategy and Rate of Improvement

Vendor Support

Microsoft Azure Machine Learning Reviews

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

Ketan S.

Role: Information Technology
Industry: Engineering
Involvement: IT Leader or Manager

Validated Review

Verified Reviewer

Submitted Mar 2024

easy & quick to setup end-to-end AI/ML solutions

Likeliness to Recommend

7 /10

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

Kumar A.

Role: Information Technology
Industry: Engineering
Involvement: End User of Application

Validated Review

Verified Reviewer

Submitted Mar 2024

Begineers Friendly

Likeliness to Recommend

9 /10

What differentiates Microsoft Azure Machine Learning from other similar products?

Microsoft Azure Machine Learning stands out for its seamless integration with the broader Azure ecosystem, offering extensive scalability, security, and flexibility, along with a rich set of pre-built tools and services for end-to-end machine learning workflows.

What is your favorite aspect of this product?

Favourite aspect of Microsoft Azure Machine Learning is its comprehensive set of features catering to diverse needs, including automated machine learning, model deployment,

What do you dislike most about this product?

I dont have any dislike.

What recommendations would you give to someone considering this product?

Prioritize understanding Azure Machine Learning's pricing, ensure compatibility with your tech stack, and leverage its extensive documentation and community support for successful adoption.

Pros

Continually Improving Product
Reliable
Efficient Service
Inspires Innovation

Microsoft Azure Machine Learning

What is Microsoft Azure Machine Learning?

Company Details

Need Assistance?

Awards & Recognition

2025 Data Quadrant Champion

2024 Emotional Footprint Champion

2024 Data Quadrant Champion

2023 Emotional Footprint Champion

2023 Data Quadrant Champion

Microsoft Azure Machine Learning Ratings

90 Likeliness to Recommend

1 Since last award

100 Plan to Renew

86 Satisfaction of Cost Relative to Value

Emotional Footprint Overview

+93 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

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

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

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

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

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

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

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.

Ensembling 'Ability to combine ML models for best results.

Explainability Ability to explain/ visualize the model.

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

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 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.

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

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

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.

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.

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.

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.

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

Bir B.

Good functionalities, but the ui need improvement.

Likeliness to Recommend

Pros

Ketan S.

easy & quick to setup end-to-end AI/ML solutions

Likeliness to Recommend

Pros

Cons

Kumar A.

Begineers Friendly

Likeliness to Recommend

Pros

Most Popular Microsoft Azure Machine Learning Comparisons

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1
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Feature Ratings

Data Exploration and Visualization

Model Training

Data Pre-Processing

Model Tuning

Feature Engineering

Pre-Packaged AI/ML Services

Data Labeling

Model Monitoring and Management

Data Ingestion

Ensembling

Explainability

Vendor Capability Ratings

Quality of Features

Ease of Customization

Breadth of Features

Ease of Implementation

Ease of Data Integration

Ease of IT Administration

Availability and Quality of Training

Usability and Intuitiveness

Business Value Created

Product Strategy and Rate of Improvement

Vendor Support