Write a review temporarily disabled. Our system flagged this request as potentially automated and has disabled form submission for security reasons. If you believe this is a mistake, please contact us. We’ll be happy to help resolve the issue.

Microsoft Corporation

Microsoft Azure Machine Learning

Composite Score

8.9 /10

CX Score

9.1 /10

70 Reviews Write a Review

Claim Software

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

Need Assistance?

We're here to help you with understanding our reports and the data inside to help you make decisions.

Get Assistance

Awards & Recognition

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

Filter By

2025 Emotional Footprint Champion

Latest Award, 2025

Product Impact

Latest Award, 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.

89 Likeliness to Recommend

1
Since last award

94 Plan to Renew

6
Since last award

85 Satisfaction of Cost Relative to Value

1
Since last award

{y}

{name}

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.

+94 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

1% Neutral

97% Positive

Pros

Performance Enhancing
Reliable
Security Protects
Enables Productivity

Feature Ratings

Average 84

Pre-Packaged AI/ML Services

Model Training

Data Exploration and Visualization

Data Pre-Processing

Model Tuning

Feature Engineering

Algorithm Recommendation

Data Labeling

Model Monitoring and Management

Ensembling

Algorithm Diversity

Vendor Capability Ratings

Average 83

Ease of Data Integration

Ease of Customization

Breadth of Features

Quality of Features

Product Strategy and Rate of Improvement

Ease of IT Administration

Ease of Implementation

Usability and Intuitiveness

Availability and Quality of Training

Business Value Created

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

Mayank J.

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

Validated Review

Verified Reviewer

Submitted Apr 2026

Accelerate AI Projects with Azure ML

Likeliness to Recommend

9 /10

What differentiates Microsoft Azure Machine Learning from other similar products?

Microsoft Azure Machine Learning stand out in how it's perfectly bridge the gap between data work and production ML without forcing you into a rigid workflow. As my perspective, the end to end integration with the Azure ecosystem is a big differentiator and if you already working with tools like Synapse, Power BI or Azure Data Factory it's fits in Naturally. One more I appreciate that is the flexibility in how you build models

What is your favorite aspect of this product?

It's how smoothly it connects experimentation to production in Microsoft Azure Machine Learning is my favorite aspect and one more thing you can start work with quick exploratory work to playing around with datasets , testing model in notebooks when something actually works then you don't have to jump through hoops to deploy it.

What do you dislike most about this product?

I dislike Microsoft Azure Machine Learning is that it can fell a bit overwhelming at times and when you are trying to navigate all the features especially for the first time. One more pain point it's is the cost visibility and management

What recommendations would you give to someone considering this product?

I recommend to explore every feature right away but you will get more value by focusing on a small and clear use cases like building and deploying a single model end to end. I also suggest leaning into the Azure ecosystem if you are already using it and the real strength of ML shows up when it is integrated with tools like storage and data pipelines. In Microsoft Azure Machine learning are my biggest recommendation is to start simple and grow into it.

Pros

Reliable
Enables Productivity
Trustworthy
Client's Interest First

Cons

Less Inspiring

Sikha S.

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

Validated Review

Verified Reviewer

Submitted Mar 2026

microsoft azure machine learning

Likeliness to Recommend

10 /10

What differentiates Microsoft Azure Machine Learning from other similar products?

enterprise grade security compliance and role based access controls

What is your favorite aspect of this product?

both gui and code based interfaces accommodating teams of varying skill levels

What do you dislike most about this product?

the ui sometimes feels slow or has navigational difficulties

What recommendations would you give to someone considering this product?

strictly enforce access controls and audit logging in accordance with security and compliance requirements

Pros

Helps Innovate
Reliable
Performance Enhancing
Enables Productivity

Microsoft Azure Machine Learning

What is Microsoft Azure Machine Learning?

Company Details

Need Assistance?

Awards & Recognition

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

89 Likeliness to Recommend

1 Since last award

94 Plan to Renew

6 Since last award

85 Satisfaction of Cost Relative to Value

1 Since last award

Emotional Footprint Overview

+94 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 Exploration and Visualization Ability to visually manipulate, interact with, and explore data, and perform basic descriptive statistics and pattern detection.

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.

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

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.

Ensembling 'Ability to combine ML models for best results.

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

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.

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.

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.

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.

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

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.

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.

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

Mayank J.

Accelerate AI Projects with Azure ML

Likeliness to Recommend

Pros

Cons

Sikha S.

microsoft azure machine learning

Likeliness to Recommend

Pros

Most Popular Microsoft Azure Machine Learning Comparisons

Google Cloud Vertex AI

MathWorks MATLAB

AWS Machine Learning

Databricks Data Intelligence Platform

Altair RapidMiner

DataRobot AI Platform

1
Since last award

6
Since last award

1
Since last award

Feature Ratings

Pre-Packaged AI/ML Services

Model Training

Data Exploration and Visualization

Data Pre-Processing

Model Tuning

Feature Engineering

Algorithm Recommendation

Data Labeling

Model Monitoring and Management

Ensembling

Algorithm Diversity

Vendor Capability Ratings

Ease of Data Integration

Ease of Customization

Breadth of Features

Quality of Features

Product Strategy and Rate of Improvement

Ease of IT Administration

Ease of Implementation

Usability and Intuitiveness

Availability and Quality of Training

Business Value Created

Vendor Support