AWS Machine Learning Customer Reviews 2023

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.

84 Likeliness to Recommend

Up 1
Since last award

93 Plan to Renew

69 Satisfaction of Cost Relative to Value

Emotional Footprint Overview

+74 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

12% Neutral

88% Positive

Pros

Continually Improving Product
Reliable
Respectful
Efficient Service

Cons

Commodity Features
Vendor Friendly Policies

Feature Ratings

Average 73

Performance and Scalability

80

Ensembling

79

Pre-Packaged AI/ML Services

78

Data Pre-Processing

78

Data Ingestion

77

Model Training

73

Data Labeling

72

Feature Engineering

72

Algorithm Recommendation

71

Data Exploration and Visualization

70

Model Tuning

68

Vendor Capability Ratings

Average 74

Quality of Features

81

Breadth of Features

80

Ease of Data Integration

79

Business Value Created

78

Ease of Implementation

78

Product Strategy and Rate of Improvement

74

Vendor Support

73

Ease of Customization

72

Ease of IT Administration

70

Usability and Intuitiveness

68

Availability and Quality of Training

60

AWS Machine Learning Reviews

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

Mukesh T.

Role: Consultant
Industry: Healthcare
Involvement: End User of Application

Validated Review

Verified Reviewer

Submitted Nov 2022

Easy to use and it's fantastic product.

Likeliness to Recommend

7 / 10

What differentiates AWS Machine Learning from other similar products?

Better to use AWS machine learning if you are using other AWS services as well as you get everything under a same roof.

What is your favorite aspect of this product?

Better support from AWS technical team

What do you dislike most about this product?

Needs to improve models

What recommendations would you give to someone considering this product?

Better to use AWS ML as they have good technical support.

Pros

Helps Innovate
Performance Enhancing
Trustworthy
Unique Features

Asim S.

Role: Sales Marketing
Industry: Banking
Involvement: IT Leader or Manager

Validated Review

Verified Reviewer

Submitted Nov 2022

Fantastic product!

Likeliness to Recommend

9 / 10

What differentiates AWS Machine Learning from other similar products?

The Sagemaker has an amazing set of features.

What is your favorite aspect of this product?

Model Development from a set of model images.

What do you dislike most about this product?

the pricing can shoot.

What recommendations would you give to someone considering this product?

Properly look at the pricing plan.

Pros

Reliable
Client's Interest First
Appreciates Incumbent Status
Helps Innovate

Cons

Less Productive
Less Caring
Less Fair

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AWS Machine Learning

AWS Machine Learning

What is AWS Machine Learning?

Company Details

Need Assistance?

AWS Machine Learning Ratings

84 Likeliness to Recommend

Up 1Since last award

93 Plan to Renew

69 Satisfaction of Cost Relative to Value

Emotional Footprint Overview

+74 Net Emotional Footprint

How much do users love AWS Machine Learning?

Pros

Cons

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.

Ensembling 'Ability to combine ML models for best results.

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.

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.

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

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

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

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

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.

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

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.

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.

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.

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

Reddi Bhaskar K.

Easy to use, but a bit pricey.

Likeliness to Recommend

Pros

Mukesh T.

Easy to use and it's fantastic product.

Likeliness to Recommend

Pros

Asim S.

Fantastic product!

Likeliness to Recommend

Pros

Cons

Most Popular AWS Machine Learning Comparisons

MathWorks Matlab

Google Cloud Vertex AI

Alteryx

DataRobot AI Cloud

Dataiku

Databricks Lakehouse Platform

Up 1
Since last award

Feature Ratings

Performance and Scalability

Ensembling

Pre-Packaged AI/ML Services

Data Pre-Processing

Data Ingestion

Model Training

Data Labeling

Feature Engineering

Algorithm Recommendation

Data Exploration and Visualization

Model Tuning

Vendor Capability Ratings

Quality of Features

Breadth of Features

Ease of Data Integration

Business Value Created

Ease of Implementation

Product Strategy and Rate of Improvement

Vendor Support

Ease of Customization

Ease of IT Administration

Usability and Intuitiveness

Availability and Quality of Training