Amazon

AWS Machine Learning

8.0 /10

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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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.

85 Likeliness to Recommend

89 Plan to Renew

74 Satisfaction of Cost Relative to Value

2
Since last award

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Emotional Footprint Overview

+83 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

9% Neutral

91% Positive

Pros

Reliable
Security Protects
Respectful
Continually Improving Product

Feature Ratings

Average 77

Performance and Scalability

Data Ingestion

Pre-Packaged AI/ML Services

Data Pre-Processing

Feature Engineering

Data Exploration and Visualization

Algorithm Recommendation

Ensembling

Data Labeling

Model Training

Model Tuning

Vendor Capability Ratings

Average 77

Ease of Data Integration

Quality of Features

Business Value Created

Ease of Implementation

Vendor Support

Breadth of Features

Product Strategy and Rate of Improvement

Ease of Customization

Usability and Intuitiveness

Ease of IT Administration

Availability and Quality of Training

AWS Machine Learning Reviews

Jitendra l.

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

Validated Review

Verified Reviewer

Submitted Jan 2024

"Awesome product"

Likeliness to Recommend

10 /10

What differentiates AWS Machine Learning from other similar products?

AWS Machine Learning differentiates itself with its user-friendly and scalable approach to machine learning. Its key features include automated model training, deployment, and management, allowing users to build machine learning models without the need for extensive expertise. The integration with other AWS services, such as S3 and SageMaker, enhances its versatility. Additionally, AWS Machine Learning offers cost-effective pricing and supports a wide range of use cases, making it a compelling choice for users within the AWS ecosystems.

What is your favorite aspect of this product?

I appreciate AWS Machine Learning for its user-friendly interface, automation features, and seamless integration with other AWS services. The accessibility it provides to users with varying levels of machine learning expertise is a notable aspect, making it easier to implement machine learning solutions within the AWS environment

What do you dislike most about this product?

Nothing to dislike

What recommendations would you give to someone considering this product?

For those considering AWS Machine Learning, it's important to clearly define your machine learning objectives and use cases. Evaluate the user-friendliness of the platform and its compatibility with your existing AWS infrastructure. Take advantage of the automated model training and deployment features to streamline the machine learning workflow. Consider factors like scalability and cost-effectiveness based on your project's requirements. Lastly, explore available documentation and support resources to optimize your experience with AWS Machine Learning.

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Gaurav K.

Role: Information Technology
Industry: Communications
Involvement: Business Leader or Manager

Validated Review

Verified Reviewer

Submitted Oct 2023

Awesome Product

Likeliness to Recommend

9 /10

What differentiates AWS Machine Learning from other similar products?

one of the best product of AWS ML is sage maker which gets easily deployed using couple of Cloudformation scripts Sage maker pilot allows to use automatic model creation so efficiently. Real time and batch inferencing allows devs to obtain predictions interactively Easy UI to spin up sagemaker instances and train your ML models on that

What is your favorite aspect of this product?

Real time and batch inferencing allows devs to obtain predictions interactively

What do you dislike most about this product?

No issues so far with the product

What recommendations would you give to someone considering this product?

Make sure you are not keeping instances on/off for longer period of time , have some automation policies to clear the instances that are not being used

Pros

Enables Productivity
Security Protects
Helps Innovate
Reliable

Vaibhav B.

Role: Industry Specific Role
Industry: Biotechnology
Involvement: IT Development, Integration, and Administration

Validated Review

Verified Reviewer

Submitted Oct 2023

Easy to use. A lot of features, but pricey.

Likeliness to Recommend

9 /10

What differentiates AWS Machine Learning from other similar products?

AWS has established itself in the market! everyone understands AWS better than other cloud providers.

What is your favorite aspect of this product?

great UI/UX

What do you dislike most about this product?

a lot of features. really confusing .

What recommendations would you give to someone considering this product?

Do try it! i personally found it more user friendly than GCP.

Pros

Helps Innovate
Reliable
Performance Enhancing
Fair

AWS Machine Learning

What is AWS Machine Learning?

Company Details

Need Assistance?

Awards & Recognition

AWS Machine Learning Ratings

85 Likeliness to Recommend

89 Plan to Renew

74 Satisfaction of Cost Relative to Value

2 Since last award

Emotional Footprint Overview

+83 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

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

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.

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

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

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

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

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

Ensembling 'Ability to combine ML models for best results.

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.

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

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.

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.

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.

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.

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.

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.

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.

AWS Machine Learning Reviews

Jitendra l.

"Awesome product"

Likeliness to Recommend

Pros

Gaurav K.

Awesome Product

Likeliness to Recommend

Pros

Vaibhav B.

Easy to use. A lot of features, but pricey.

Likeliness to Recommend

Pros

Most Popular AWS Machine Learning Comparisons

Google Cloud Vertex AI

MathWorks Matlab

Microsoft Azure Machine Learning

Alteryx

Databricks Data Intelligence Platform

DataRobot AI Platform

2
Since last award

Feature Ratings

Performance and Scalability

Data Ingestion

Pre-Packaged AI/ML Services

Data Pre-Processing

Feature Engineering

Data Exploration and Visualization

Algorithm Recommendation

Ensembling

Data Labeling

Model Training

Model Tuning

Vendor Capability Ratings

Ease of Data Integration

Quality of Features

Business Value Created

Ease of Implementation

Vendor Support

Breadth of Features

Product Strategy and Rate of Improvement

Ease of Customization

Usability and Intuitiveness

Ease of IT Administration

Availability and Quality of Training