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

Rushikesh M.

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

Validated Review

Verified Reviewer

Submitted Apr 2022

Easy, scalable, more control to developers

Likeliness to Recommend

8 /10

What differentiates AWS Machine Learning from other similar products?

The integration with data sources across the board as well as good support with model deployment and monitoring really gives aws ml an upper edge Its easier to spin up stand alone notebook instances with custom kernels that suits the dev environment. The lifecycle configuration provides better opportunity and control over setup and maintenance for model training AWS feature stores provides unique set of features for complex ML operations in Natural Language Processing and Computer Vision ML space.The integration of ML services to applications downstream and hosting is smooth. Overall the product really eases Ml development

What is your favorite aspect of this product?

Sagemaker notebook instances. Easy to spin up, scale and deploy ml models It is also to replicate and link with source control repos.

What do you dislike most about this product?

The model deployment services and monitoring can be a bit better with more control to developers to track and monitor some unique aspects

What recommendations would you give to someone considering this product?

Light weight POC development can be easily scaled and deployed, if you are in need of something like this, this is your product

Pros

Reliable
Efficient Service
Saves Time
Acts with Integrity

Cons

Less Transparent
Commodity Features
Vendor Friendly Policies

Vicent A.

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

Validated Review

Verified Reviewer

Submitted Feb 2022

It's good to start with machine learning!

Likeliness to Recommend

8 /10

What differentiates AWS Machine Learning from other similar products?

All others AWS services involved to create a good products

What is your favorite aspect of this product?

is fast to deploy a model

What do you dislike most about this product?

a very few options

What recommendations would you give to someone considering this product?

Don't lose your hope at first try

Pros

Performance Enhancing
Enables Productivity
Saves Time
Includes Product Enhancements

Cons

Commodity Features
Vendor Friendly Policies

Rushikesh G.

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

Validated Review

Verified Reviewer

Submitted Jul 2021

vast variety of updates

Likeliness to Recommend

10 /10

What differentiates AWS Machine Learning from other similar products?

AWS offers the broadest and deepest set of machine learning services and supporting cloud infrastructure, putting machine learning in the hands of every developer, data scientist and expert practitioner

What is your favorite aspect of this product?

Intelligent document processing

What do you dislike most about this product?

High Level of Error Susceptibility

What recommendations would you give to someone considering this product?

Yes, It is good in the market

Pros

Performance Enhancing
Fair
Unique Features
Altruistic

AWS Machine Learning

What is AWS Machine Learning?

Company Details

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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

Rushikesh M.

Easy, scalable, more control to developers

Likeliness to Recommend

Pros

Cons

Vicent A.

It's good to start with machine learning!

Likeliness to Recommend

Pros

Cons

Rushikesh G.

vast variety of updates

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