Amazon

AWS Machine Learning

Composite Score

8.5 /10

CX Score

8.7 /10

60 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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2024 Emotional Footprint Champion

Latest Award, 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.

88 Likeliness to Recommend

1
Since last award

93 Plan to Renew

1
Since last award

79 Satisfaction of Cost Relative to Value

1
Since last award

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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.

+89 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

6% Neutral

94% Positive

Pros

Continually Improving Product
Respectful
Efficient Service
Security Protects

Feature Ratings

Average 78

Pre-Packaged AI/ML Services

Performance and Scalability

Data Pre-Processing

Data Ingestion

Openness and Flexibility

Algorithm Recommendation

Feature Engineering

Model Tuning

Algorithm Diversity

Data Labeling

Model Training

Vendor Capability Ratings

Average 78

Quality of Features

Ease of Implementation

Ease of Data Integration

Vendor Support

Business Value Created

Breadth of Features

Ease of Customization

Ease of IT Administration

Product Strategy and Rate of Improvement

Usability and Intuitiveness

Availability and Quality of Training

AWS Machine Learning Reviews

Sashank M.

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

Validated Review

Verified Reviewer

Submitted Jun 2023

Ease to use and Best in segment

Likeliness to Recommend

9 /10

What differentiates AWS Machine Learning from other similar products?

Broad Range of Services: AWS offers a wide array of machine learning services, catering to different user requirements and expertise levels. Scalability and Flexibility: AWS Machine Learning provides highly scalable infrastructure, enabling users to process large volumes of data and train complex machine learning models efficiently. Integration with AWS Ecosystem: One significant advantage of AWS Machine Learning is its seamless integration with other AWS services. Flexibility in Model Development: AWS Machine Learning services support various popular machine learning frameworks, such as TensorFlow, PyTorch, and MXNet.

What is your favorite aspect of this product?

Managed Services: AWS offers fully managed services, such as Amazon SageMaker, which handle many operational aspects of machine learning. These managed services take care of infrastructure provisioning, automatic scaling, model deployment, and monitoring, Cost Optimization: AWS provides several options to optimize costs when utilizing machine learning services. Users can choose from a variety of instance types and pricing options based on their specific needs.

What do you dislike most about this product?

Complexity for Beginners: While AWS Machine Learning offers a range of services and features, the platform can be complex for users who are new to machine learning or cloud computing. Cost Management: While AWS offers cost optimization tools and options, managing costs can still be a concern, particularly for users who are new to cloud services. Vendor Lock-In: AWS Machine Learning is a part of the Amazon Web Services ecosystem, which means that using these services ties users to the AWS platform.

What recommendations would you give to someone considering this product?

Learn the Basics: Familiarize yourself with the fundamental concepts and principles of machine learning, as well as the basics of cloud computing. Understand Your Needs: Before diving into AWS Machine Learning, clearly define your goals and requirements. Leverage AWS Documentation and Resources: AWS provides comprehensive documentation, tutorials, and guides to help users get started with AWS Machine Learning. Experiment with Sample Projects: AWS offers various sample projects and examples that can serve as a starting point for your own machine learning applications.

Pros

Helps Innovate
Continually Improving Product
Reliable
Enables Productivity

Role: Consultant
Industry: Engineering
Involvement: IT Development, Integration, and Administration

Validated Review

Anonymous Reviewer

Submitted Mar 2023

The AWS Machine learning tools are remarkable.

Likeliness to Recommend

10 /10

Pros

Effective Service
Caring
Acts with Integrity
Helps Innovate

Reddi Bhaskar K.

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

Validated Review

Verified Reviewer

Submitted Mar 2023

Easy to use, but a bit pricey.

Likeliness to Recommend

9 /10

What differentiates AWS Machine Learning from other similar products?

All the ML related services are available in AWS

What is your favorite aspect of this product?

Labeling, rekognition of objectives and auto modeling

What do you dislike most about this product?

Live capture the images

What recommendations would you give to someone considering this product?

It's easy to implementing the ML algorithms

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

AWS Machine Learning

What is AWS Machine Learning?

Company Details

Need Assistance?

Awards & Recognition

2024 Emotional Footprint Champion

AWS Machine Learning Ratings

88 Likeliness to Recommend

1 Since last award

93 Plan to Renew

1 Since last award

79 Satisfaction of Cost Relative to Value

1 Since last award

Emotional Footprint Overview

+89 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.

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.

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

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

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

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

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

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 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.

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 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.

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.

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

Sashank M.

Ease to use and Best in segment

Likeliness to Recommend

Pros

The AWS Machine learning tools are remarkable.

Likeliness to Recommend

Pros

Reddi Bhaskar K.

Easy to use, but a bit pricey.

Likeliness to Recommend

Pros

Most Popular AWS Machine Learning Comparisons

Google Cloud Vertex AI

MathWorks MATLAB

Microsoft Azure Machine Learning

Databricks Data Intelligence Platform

DataRobot AI Platform

KNIME Analytics Platform

1
Since last award

1
Since last award

1
Since last award

Feature Ratings

Pre-Packaged AI/ML Services

Performance and Scalability

Data Pre-Processing

Data Ingestion

Openness and Flexibility

Algorithm Recommendation

Feature Engineering

Model Tuning

Algorithm Diversity

Data Labeling

Model Training

Vendor Capability Ratings

Quality of Features

Ease of Implementation

Ease of Data Integration

Vendor Support

Business Value Created

Breadth of Features

Ease of Customization

Ease of IT Administration

Product Strategy and Rate of Improvement

Usability and Intuitiveness

Availability and Quality of Training