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
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Since last award
93 Plan to Renew
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Since last award
79 Satisfaction of Cost Relative to Value
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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
- Continually Improving Product
- Respectful
- Efficient Service
- Security Protects
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
Performance and Scalability
Data Pre-Processing
Data Ingestion
Openness and Flexibility
Algorithm Recommendation
Feature Engineering
Model Tuning
Algorithm Diversity
Data Labeling
Model Training
Vendor Capability Ratings
Quality of Features
Ease of Implementation
Ease of Data Integration
Vendor Support
Business Value Created
Breadth of Features
Ease of Customization
Ease of IT Administration
Product Strategy and Rate of Improvement
Usability and Intuitiveness
Availability and Quality of Training
AWS Machine Learning Reviews
Arun Prakash G.
- Role: Information Technology
- Industry: Communications
- Involvement: Initial Implementation
Submitted Jan 2025
Fantastic product
Likeliness to Recommend
What differentiates AWS Machine Learning from other similar products?
Nothing as such
What is your favorite aspect of this product?
Cost effectiveness
What do you dislike most about this product?
Nothing as such
What recommendations would you give to someone considering this product?
Cost effectiveness
Pros
- Helps Innovate
- Continually Improving Product
- Performance Enhancing
- Enables Productivity
Bhavik M.
- Role: Information Technology
- Industry: Education
- Involvement: IT Leader or Manager
Submitted Jan 2025
Powerful and flexible, but requires AWS expertise
Likeliness to Recommend
What differentiates AWS Machine Learning from other similar products?
AWS Machine Learning stands out for its seamless integration with AWS services, end-to-end support through SageMaker, and flexibility across frameworks and tools.
What is your favorite aspect of this product?
Amazon SageMaker's end-to-end ML capabilities streamline the entire workflow, making it efficient and scalable for all skill levels.
What do you dislike most about this product?
Nothing specific to dislike
What recommendations would you give to someone considering this product?
Start small with AWS Machine Learning, leverage SageMaker for scalability, and utilize AWS's rich ecosystem to maximize efficiency.
Pros
- Helps Innovate
- Reliable
- Performance Enhancing
- Enables Productivity
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
