Microsoft Corporation

Microsoft Azure Machine Learning

Composite Score

8.8 /10

CX Score

9.1 /10

51 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 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

{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.

+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

Avinash G.

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

Validated Review

Verified Reviewer

Submitted Mar 2024

Really awesome service easy to use

Likeliness to Recommend

10 /10

What differentiates Microsoft Azure Machine Learning from other similar products?

Azure service is mind blowing it's GPU power and all the services that provided by azure

What is your favorite aspect of this product?

Service for AI integration and some High GPU processing

What do you dislike most about this product?

There is nothing to dislike but pricing is little bit more but anyway I don't mind it and really like it

What recommendations would you give to someone considering this product?

If you're building large AI model or ML model go for it

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Swastik P.

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

Validated Review

Verified Reviewer

Submitted Mar 2024

Confusing at start but fantastic product.

Likeliness to Recommend

9 /10

What differentiates Microsoft Azure Machine Learning from other similar products?

The n number of tools it has for different purposes, which can be used in any given scenario.

What is your favorite aspect of this product?

How well it can analyze different and advanced data.

What do you dislike most about this product?

it's just a bit complicated to get used to.

What recommendations would you give to someone considering this product?

Do go through the tutorial.

Pros

Continually Improving Product
Performance Enhancing
Fair
Altruistic

Jay S.

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

Validated Review

Verified Reviewer

Submitted Feb 2024

It is good for use . It also time efficient.

Likeliness to Recommend

9 /10

What differentiates Microsoft Azure Machine Learning from other similar products?

AWS machine learning

What is your favorite aspect of this product?

Delightful

What do you dislike most about this product?

Very good product

What recommendations would you give to someone considering this product?

Use it mostly because it time efficient

Pros

Performance Enhancing
Enables Productivity
Trustworthy
Unique Features

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

Avinash G.

Really awesome service easy to use

Likeliness to Recommend

Pros

Swastik P.

Confusing at start but fantastic product.

Likeliness to Recommend

Pros

Jay S.

It is good for use . It also time efficient.

Likeliness to Recommend

Pros

Most Popular Microsoft Azure Machine Learning Comparisons

Google Cloud Vertex AI

MathWorks MATLAB

AWS Machine Learning

Databricks Data Intelligence Platform

DataRobot AI Platform

Alteryx

1
Since last award

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