Amazon

AWS Machine Learning

8.2 /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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Awards & Recognition

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

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0 Top Rated Capabilities

2 Top Rated Features

Latest Award, 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.

86 Likeliness to Recommend

1
Since last award

91 Plan to Renew

2
Since last award

76 Satisfaction of Cost Relative to Value

2
Since last award

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Emotional Footprint Overview

+84 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

8% Neutral

92% Positive

Pros

Reliable
Security Protects
Respectful
Continually Improving Product

Feature Ratings

Average 77

Performance and Scalability

Pre-Packaged AI/ML Services

Data Ingestion

Data Pre-Processing

Feature Engineering

Data Labeling

Algorithm Recommendation

Data Exploration and Visualization

Ensembling

Model Training

Model Tuning

Vendor Capability Ratings

Average 77

Ease of Data Integration

Quality of Features

Business Value Created

Breadth of Features

Ease of Implementation

Vendor Support

Usability and Intuitiveness

Ease of Customization

Ease of IT Administration

Product Strategy and Rate of Improvement

Availability and Quality of Training

AWS Machine Learning Reviews

Sidhant N.

Role: Student Academic
Industry: Technology
Involvement: IT Leader or Manager

Validated Review

Verified Reviewer

Submitted Jul 2024

AWS ML: Desired Features for Future Development

Likeliness to Recommend

9 /10

What differentiates AWS Machine Learning from other similar products?

AWS Machine Learning stands out due to its extensive and scalable cloud infrastructure, seamless integration with other AWS services, and a broad range of pre-built machine learning models and tools

What is your favorite aspect of this product?

My favorite aspect of AWS Machine Learning is its seamless integration with other AWS services

What do you dislike most about this product?

One aspect I dislike about AWS Machine Learning is the complexity of its pricing structure. The cost can be difficult to predict due to the variety of services and their usage-based pricing models.

What recommendations would you give to someone considering this product?

Understand AWS pricing to manage costs effectively. Utilize free tiers for initial testing. Leverage AWS’s extensive documentation and training. Integrate with other AWS services for efficiency.

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Ritika B.

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

Validated Review

Verified Reviewer

Submitted May 2024

Extremely satisfied, Has excellent services!

Likeliness to Recommend

10 /10

What differentiates AWS Machine Learning from other similar products?

It has a well architected framework. Which helps a lot in decision making. It has guides which ask the right questions for a better evaluation.

What is your favorite aspect of this product?

It's quick automation is the best feature. Also it's capabilities to handle such huge data.

What do you dislike most about this product?

The cost, would love if the cost could be reduced.

What recommendations would you give to someone considering this product?

Go through the initial trainings before you begin. As it would give a much better understanding of the product.

Pros

Helps Innovate
Performance Enhancing
Enables Productivity
Trustworthy

Abhay C.

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

Validated Review

Verified Reviewer

Submitted May 2024

Strong, Entire, and Complicated

Likeliness to Recommend

8 /10

What differentiates AWS Machine Learning from other similar products?

Scalability, flexibility, and an extensive and integrated set of services are what make AWS Machine Learning unique. It provides a vast array of tools, ranging from pre-built AI services like Rekognition and Comprehend to SageMaker for complete model building. Furthermore, its smooth connection with the larger AWS ecosystem offers strong infrastructure and comprehensive support for large-scale machine learning model deployment.

What is your favorite aspect of this product?

Amazon SageMaker is my favorite feature of AWS Machine Learning. It greatly streamlines the workflow by providing an end-to-end solution for creating, honing, and implementing machine learning models. It is very strong and easy to use for both novice and expert data scientists due to its ability to expand effortlessly and connect with other AWS services.

What do you dislike most about this product?

The complexity and high learning curve of AWS Machine Learning are the most annoying features for newcomers. It can be intimidating to sort through the multitude of services and comprehend how they all work together. Furthermore, the cost structure might be complicated, which makes it difficult to anticipate costs precisely without careful preparation and observation.

What recommendations would you give to someone considering this product?

Start with the free tier of AWS and use its introductory lessons to familiarize yourself without spending any money. Take advantage of seamless connectivity with other AWS services and monitor spending with tools like AWS Cost Explorer. Join the AWS ML community to receive guidance and best practices.

Pros

Continually Improving Product
Reliable
Unique Features
Efficient Service

AWS Machine Learning

What is AWS Machine Learning?

Company Details

Need Assistance?

Awards & Recognition

AWS Machine Learning Ratings

86 Likeliness to Recommend

1 Since last award

91 Plan to Renew

2 Since last award

76 Satisfaction of Cost Relative to Value

2 Since last award

Emotional Footprint Overview

+84 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.

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

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

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.

Ensembling 'Ability to combine ML models for best results.

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.

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 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.

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 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.

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

Sidhant N.

AWS ML: Desired Features for Future Development

Likeliness to Recommend

Pros

Ritika B.

Extremely satisfied, Has excellent services!

Likeliness to Recommend

Pros

Abhay C.

Strong, Entire, and Complicated

Likeliness to Recommend

Pros

Most Popular AWS Machine Learning Comparisons

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Microsoft Azure Machine Learning

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Databricks Data Intelligence Platform

1
Since last award

2
Since last award

2
Since last award

Feature Ratings

Performance and Scalability

Pre-Packaged AI/ML Services

Data Ingestion

Data Pre-Processing

Feature Engineering

Data Labeling

Algorithm Recommendation

Data Exploration and Visualization

Ensembling

Model Training

Model Tuning

Vendor Capability Ratings

Ease of Data Integration

Quality of Features

Business Value Created

Breadth of Features

Ease of Implementation

Vendor Support

Usability and Intuitiveness

Ease of Customization

Ease of IT Administration

Product Strategy and Rate of Improvement

Availability and Quality of Training