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.
88 Likeliness to Recommend
92 Plan to Renew
81 Satisfaction of Cost Relative to Value
1
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.
+92 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
- Efficient Service
- Respectful
- Includes Product Enhancements
- Reliable
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
Positive
Feature Ratings
Pre-Packaged AI/ML Services
Data Pre-Processing
Performance and Scalability
Algorithm Diversity
Feature Engineering
Data Labeling
Model Training
Openness and Flexibility
Model Tuning
Algorithm Recommendation
Ensembling
Vendor Capability Ratings
Quality of Features
Business Value Created
Ease of Data Integration
Vendor Support
Breadth of Features
Ease of Implementation
Ease of Customization
Product Strategy and Rate of Improvement
Ease of IT Administration
Usability and Intuitiveness
Availability and Quality of Training
AWS Machine Learning Reviews
Jefferson A.
- Role: Industry Specific Role
- Industry: Engineering
- Involvement: IT Development, Integration, and Administration
Submitted Jan 2025
"Powerful and scalable, but complex and costly
Likeliness to Recommend
What differentiates AWS Machine Learning from other similar products?
AWS Machine Learning stands out from other platforms with its unmatched scalability, deep integration with the broader AWS ecosystem, and extensive range of services, including SageMaker for end-to-end machine learning workflows. Its flexibility allows users to choose between pre-built AI services, custom model development, or infrastructure for specialized applications. Additionally, features like automated model tuning, explainability tools, and seamless data ingestion via AWS services differentiate it, though its pricing and complexity may pose challenges for smaller teams.
What is your favorite aspect of this product?
The seamless integration of AWS Machine Learning with the broader AWS ecosystem, enabling efficient data ingestion, scalable model deployment, and end-to-end automation, is its standout feature.
What do you dislike most about this product?
I find the interface of SageMaker Studio somewhat overwhelming at times, with too many features spread across multiple sections, making it harder to navigate and focus on specific tasks efficiently.
What recommendations would you give to someone considering this product?
If you're considering the AWS Machine Learning platform, here are a few personalized recommendations based on my experience: Understand the AWS Ecosystem: AWS has a broad array of services beyond just machine learning, so familiarize yourself with the core AWS tools like S3, EC2, and IAM. These are often essential for integrating your machine learning workflows. Start with SageMaker: If you’re new to the platform, begin with SageMaker, as it provides a user-friendly environment to build, train, and deploy models. It will help you get acquainted with the platform's tools without getting lost in the complexity of other AWS services.
Pros
- Helps Innovate
- Reliable
- Performance Enhancing
- Enables Productivity
- Role: Information Technology
- Industry: Energy
- Involvement: IT Development, Integration, and Administration
Submitted Nov 2024
Fantastic Service with lot of features
Likeliness to Recommend
Pros
- Reliable
- Enables Productivity
- Trustworthy
- Saves Time
Jeya S.
- Role: Information Technology
- Industry: Technology
- Involvement: IT Development, Integration, and Administration
Submitted Nov 2024
Trust worthy and Flexible product, Easy to use.
Likeliness to Recommend
What differentiates AWS Machine Learning from other similar products?
AWS offers a wide range of pre-built models, customizable solutions, and fully managed services like SageMaker, which simplify model development, training, and deployment.
What is your favorite aspect of this product?
My favorite aspect is it allows both novice users and experienced data scientists to easily build, train, and deploy machine learning models at scale, without worrying about infrastructure.
What do you dislike most about this product?
Not Applicable much!
What recommendations would you give to someone considering this product?
Trust worthy and Flexible product, Easy to use.
Pros
- Continually Improving Product
- Reliable
- Performance Enhancing
- Enables Productivity
