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Amazon

AWS Machine Learning

Composite Score

8.6 /10

CX Score

8.9 /10

73 Reviews Write a Review

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What is AWS Machine Learning?

Amazon Machine Learning is an Amazon Web Services product that allows a developer to discover patterns in end-user data through algorithms, construct mathematical models based on these patterns and then create and implement predictive applications.

Company Details

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Awards & Recognition

AWS Machine Learning won the following awards in the Machine Learning Platforms category

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2025 Emotional Footprint Champion

Latest Award, 2025

2025 Data Quadrant Champion

2025

1 Top Rated Capabilities

1 Top Rated Features

2025

2024 Emotional Footprint Champion

2024

0 Top Rated Capabilities

2 Top Rated Features

2024

0 Top Rated Capabilities

1 Top Rated Features

2023

AWS 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 AWS 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.

87 Likeliness to Recommend

1
Since last award

91 Plan to Renew

3
Since last award

81 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.

+91 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 AWS Machine Learning?

0% Negative

5% Neutral

95% Positive

Pros

Continually Improving Product
Respectful
Efficient Service
Effective Service

Feature Ratings

Average 78

Pre-Packaged AI/ML Services

Performance and Scalability

Data Pre-Processing

Openness and Flexibility

Data Ingestion

Algorithm Diversity

Feature Engineering

Algorithm Recommendation

Model Tuning

Data Labeling

Model Training

Vendor Capability Ratings

Average 78

Quality of Features

Ease of Data Integration

Ease of Implementation

Vendor Support

Business Value Created

Breadth of Features

Ease of IT Administration

Product Strategy and Rate of Improvement

Ease of Customization

Usability and Intuitiveness

Availability and Quality of Training

AWS Machine Learning Reviews

Monika C.

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

Validated Review

Verified Reviewer

Submitted Apr 2024

Likeliness to Recommend

8 /10

Pros

Continually Improving Product
Reliable
Enables Productivity
Unique Features

Ansh K.

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

Validated Review

Verified Reviewer

Submitted Apr 2024

Sure to kill in the market

Likeliness to Recommend

9 /10

What differentiates AWS Machine Learning from other similar products?

Comprehensive set of AI and resources, enabling users to gain deeper insights from their data

What is your favorite aspect of this product?

AWS provides support at every stage of the machine learning

What do you dislike most about this product?

Inconsistency between the services provided

What recommendations would you give to someone considering this product?

Can go used this product as it's beginner friendly and have greater aspect also in the future

Pros

Helps Innovate
Reliable
Enables Productivity
Trustworthy

Jake W.

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

Validated Review

Verified Reviewer

Submitted Mar 2026

Reliable Machine Learning Platform

Likeliness to Recommend

9 /10

What differentiates AWS Machine Learning from other similar products?

‎Architectural flexibility is the real differentiator. It also stands out by offering a multi-vendor model marketplace via a single API that allows us to switch between models from Anthropic Meta Mistral and Amazon without changing code, and this all comes under the feature called Amazon Bedrock.‎

What is your favorite aspect of this product?

‎What I find most compelling about the AWS Machine Learning ecosystem is its ability to meet my needs, whether there is a need of high level simplicity of an API or the granular control of custom silicon. Having a single source of truth for data and models protected by mature security like Bedrock Guardrails makes it much easier to move from a cool experiment to a compliant production-ready application.

What do you dislike most about this product?

‎Features like Bedrock Knowledge Bases are black boxes. They offer simplicity but lock into specific chunking and retrieval strategies, which defeats the purpose of using a managed platform in the first place.

What recommendations would you give to someone considering this product?

I would recommend you use the integrated Amazon Q assistant within the IDE or the AWS Console, as it is specifically tuned to help with architecture recommendations and can automate much of the boilerplate code needed to connect S3 buckets to ML pipelines.

Pros

Continually Improving Product
Reliable
Performance Enhancing
Enables Productivity

AWS Machine Learning

What is AWS Machine Learning?

Company Details

Need Assistance?

Awards & Recognition

2025 Emotional Footprint Champion

2025 Data Quadrant Champion

2024 Emotional Footprint Champion

AWS Machine Learning Ratings

87 Likeliness to Recommend

1 Since last award

91 Plan to Renew

3 Since last award

81 Satisfaction of Cost Relative to Value

Emotional Footprint Overview

+91 Net Emotional Footprint

How much do users love AWS 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.

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

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

Openness and Flexibility Integration with open-source and 3P resources (languages, frameworks, libraries, etc.)

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.

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.

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

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

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

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

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

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.

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.

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 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.

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.

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.

AWS Machine Learning Reviews

Monika C.

Likeliness to Recommend

Pros

Ansh K.

Sure to kill in the market

Likeliness to Recommend

Pros

Jake W.

Reliable Machine Learning Platform

Likeliness to Recommend

Pros

Most Popular AWS Machine Learning Comparisons

Google Cloud Vertex AI

MathWorks MATLAB

Microsoft Azure Machine Learning

Databricks Data Intelligence Platform

Altair RapidMiner

DataRobot AI Platform

1
Since last award

3
Since last award

Feature Ratings

Pre-Packaged AI/ML Services

Performance and Scalability

Data Pre-Processing

Openness and Flexibility

Data Ingestion

Algorithm Diversity

Feature Engineering

Algorithm Recommendation

Model Tuning

Data Labeling

Model Training

Vendor Capability Ratings

Quality of Features

Ease of Data Integration

Ease of Implementation

Vendor Support

Business Value Created

Breadth of Features

Ease of IT Administration

Product Strategy and Rate of Improvement

Ease of Customization

Usability and Intuitiveness

Availability and Quality of Training