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Microsoft Corporation

Microsoft Azure Machine Learning

Composite Score

8.8 /10

CX Score

9.0 /10

81 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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2026 Data Quadrant Champion

Latest Award, 2026

8 Top Rated Capabilities

9 Top Rated Features

Latest Award, 2026

2025 Emotional Footprint Champion

2025

Product Impact

2025

2025 Data Quadrant Champion

2025

6 Top Rated Capabilities

6 Top Rated Features

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.

88 Likeliness to Recommend

1
Since last award

95 Plan to Renew

83 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.

+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?

1% Negative

5% Neutral

94% Positive

Pros

Performance Enhancing
Helps Innovate
Includes Product Enhancements
Reliable

Feature Ratings

Average 84

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

Average 83

Ease of Data Integration

Ease of Customization

Quality of Features

Availability and Quality of Training

Product Strategy and Rate of Improvement

Breadth of Features

Ease of Implementation

Ease of IT Administration

Usability and Intuitiveness

Vendor Support

Business Value Created

Microsoft Azure Machine Learning Reviews

Sienna W.

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

Validated Review

Verified Reviewer

Submitted Aug 2025

Fruitful Machine Learning App

Likeliness to Recommend

7 /10

What differentiates Microsoft Azure Machine Learning from other similar products?

We have managed all the learning demands through this powerful software The guidelines from this app are reputable and coherent

What is your favorite aspect of this product?

The intellectual part of this app helps us in pursuing business ideas The quality time management through automated speed is also a consideration

What do you dislike most about this product?

The objective nature of this application creates a unique opportunity

What recommendations would you give to someone considering this product?

The intellectual capacity of this application creates is remarkable

Pros

Reliable
Trustworthy
Helps Innovate
Continually Improving Product

SOMTO E.

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

Validated Review

Verified Reviewer

Submitted Jul 2025

Enterprise security

Likeliness to Recommend

9 /10

What differentiates Microsoft Azure Machine Learning from other similar products?

Microsoft Azure Machine Learning (Azure ML) stands out in the crowded ML platform space by blending enterprise-grade security with deep Microsoft ecosystem integration.

What is your favorite aspect of this product?

My favorite aspect of Azure Machine Learning is its seamless enterprise integration

What do you dislike most about this product?

UI/UX Feels Dated: The Studio interface is a maze of tabs (Experiments, Endpoints, Datastores) with slow load times.

What recommendations would you give to someone considering this product?

Only Choose AML If You: Run on Azure Already: Tight integration with Power BI, Synapse, and Office 365 is AML’s superpower. Need Hybrid/On-Prem ML: Unique strength via Azure Arc (SageMaker/Vertex can’t do this). Prioritize Compliance: HIPAA/GDPR-ready out of the box (ideal for healthcare/finance).

Pros

Helps Innovate
Performance Enhancing
Unique Features
Efficient Service

Martins A.

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

Validated Review

Verified Reviewer

Submitted Nov 2024

Great product and a huge productivity boost

Likeliness to Recommend

8 /10

What differentiates Microsoft Azure Machine Learning from other similar products?

The wealth of tools and features. Microsoft Azure Machine Learning supports the entire Machine Learning workflow from preprocessing to model deployment. It is also great for version control and tracking

What is your favorite aspect of this product?

The terminal. I do not have to wrangle with virtual environments. The platform alows me to work and collaborate with others seamlessly. This is a huge productivity boost.

What do you dislike most about this product?

I’d say the sharp learning curve. Azure Machine Learning can appear overwhelming for beginners. It is quite easy to get lost in the sea of features. This was a challenge for me as I was getting acquitted with the product.

What recommendations would you give to someone considering this product?

Start small. Make sure you have a guide. Also familiarity with basic machine learning concepts is a huge advantage

Pros

Performance Enhancing
Enables Productivity
Unique Features
Effective Service

Microsoft Azure Machine Learning

What is Microsoft Azure Machine Learning?

Company Details

Need Assistance?

Awards & Recognition

2026 Data Quadrant Champion

2025 Emotional Footprint Champion

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

88 Likeliness to Recommend

1 Since last award

95 Plan to Renew

83 Satisfaction of Cost Relative to Value

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

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

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

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

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

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

Algorithm Diversity Provides multiple diverse ready-to-use machine learning algorithms out-of-the-box.

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

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

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

Algorithm Recommendation Ability to recommend a best ML algorithm to use based on dataset characteristics.

Ensembling 'Ability to combine ML models for best results.

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

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

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.

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.

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.

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.

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

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.

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.

Microsoft Azure Machine Learning Reviews

Sienna W.

Fruitful Machine Learning App

Likeliness to Recommend

Pros

SOMTO E.

Enterprise security

Likeliness to Recommend

Pros

Martins A.

Great product and a huge productivity boost

Likeliness to Recommend

Pros

Most Popular Microsoft Azure Machine Learning Comparisons

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DataRobot AI Platform

1
Since last award

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

Availability and Quality of Training

Product Strategy and Rate of Improvement

Breadth of Features

Ease of Implementation

Ease of IT Administration

Usability and Intuitiveness

Vendor Support

Business Value Created