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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Real user data aggregated to summarize the product performance and customer experience.
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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.
86 Likeliness to Recommend
1
Since last award
93 Plan to Renew
4
Since last award
78 Satisfaction of Cost Relative to Value
4
Since last award
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?
Pros
- Reliable
- Security Protects
- Continually Improving Product
- Respectful
How to read the Emotional Footprint
The Net Emotional Footprint measures high-level user sentiment towards particular product offerings. It aggregates emotional response ratings for various dimensions of the vendor-client relationship and product effectiveness, creating a powerful indicator of overall user feeling toward the vendor and product.
While purchasing decisions shouldn't be based on emotion, it's valuable to know what kind of emotional response the vendor you're considering elicits from their users.
Footprint
Negative
Neutral
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Feature Ratings
Pre-Packaged AI/ML Services
Performance and Scalability
Data Ingestion
Data Pre-Processing
Data Exploration and Visualization
Feature Engineering
Data Labeling
Algorithm Recommendation
Model Training
Model Tuning
Openness and Flexibility
Vendor Capability Ratings
Quality of Features
Ease of Data Integration
Ease of Implementation
Vendor Support
Business Value Created
Breadth of Features
Ease of Customization
Ease of IT Administration
Usability and Intuitiveness
Product Strategy and Rate of Improvement
Availability and Quality of Training
AWS Machine Learning Reviews
Ekta S.
- Role: Information Technology
- Industry: Technology
- Involvement: End User of Application
Submitted Mar 2024
Very comprehensive product: good to use
Likeliness to Recommend
What differentiates AWS Machine Learning from other similar products?
The ensembling capability of model training along with pretrained models provided by AWS are a gamechanger. AWS ML techniques are way ahead of GCP and Azure in its functionalities and model capabilities. Sagemaker Jumpstart, Inference recommender are techniques which are the leading differentiators.
What is your favorite aspect of this product?
The Sagemaker studio is an all in one portal to go to whenever we wish to work with any ML capabilities. It provides integration with Gen AI capabilities as well. It has all the latest models integrated within itself which makes it a comprehensive product to use.
What do you dislike most about this product?
I had used AWS comprehend for developing models for one such application. AWS comprehend has pretrained models for training text data for various tasks. I see that it has limited capacity for model training and experimentation. If there would be more flexibility for hyper parameter tuning it would be worth using it then.
What recommendations would you give to someone considering this product?
AWS ML is an end to end service which can be used to work with all kinds of workloads. It is very useful and reliable service to use. Worth exploring the pretrained models which are bundled as a part of various services. It has all aspects of ML bundled up together in the best suite possible. If you are starting then start with basic models and then scale up further.
Pros
- Performance Enhancing
- Trustworthy
- Unique Features
- Effective Service
Pradeep P.
- Role: Information Technology
- Industry: Transportation
- Involvement: IT Development, Integration, and Administration
Submitted Feb 2024
AWS is a powerful tool
Likeliness to Recommend
What differentiates AWS Machine Learning from other similar products?
1. Innovative technologies 2. it is quite reliable and secure compared to other resources. 3. It is user friendly Graphical user interface
What is your favorite aspect of this product?
Highly cost effective AWS tools simplify tasks for developers. These include the AWS CLI, SDKs for languages, IDEs, and DevOps tools like AWS CloudFormation and AWS CodeDeploy. AWS introduces new technologies through research like AI, ML, serverless computing, containers, and edge computing.
What do you dislike most about this product?
1. Meeting regulatory rules like GDPR, HIPAA, or PCI DSS with AWS services can be tough. Making certain compliance may mean extra work and money putting in and overseeing security, checking, and papers. 2.Storing sensitive data online raises concerns. AWS uses security like encryption but users manage data. 3.Occasional downtime can occur on AWS. Disruptions may impact businesses relying on AWS, affecting work and customer experience.
What recommendations would you give to someone considering this product?
Must use web service tool .
Pros
- Continually Improving Product
- Performance Enhancing
- Enables Productivity
- Inspires Innovation
Jitendra L.
- Role: Information Technology
- Industry: Technology
- Involvement: End User of Application
Submitted Jan 2024
"Awesome product"
Likeliness to Recommend
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
