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
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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
Vijay I.
- Role: Information Technology
- Industry: Engineering
- Involvement: End User of Application
Submitted Oct 2022
Must needed product for AI based organisations.
Likeliness to Recommend
What differentiates AWS Machine Learning from other similar products?
AWS Machine learning platform has almost all the features that are needed for the Machine learning model development cycle. Right from data ingestion to model hosting is what makes it unique.
What is your favorite aspect of this product?
My favourite aspect of the AWS Machine learning product is the infrastructure provided by them. It provides high ram GPUs that are needed for huge model training tasks. Also, the dashboard shows the status of each training and deployed services. Easy to manage all in one place. It also has support for various ML algorithms needed for model training with minimal code.
What do you dislike most about this product?
The cost of AWS Machine learning is high when compared to other products. Its costs are based on hourly usage. The more the usage more costlier it will be. This makes it think about before choosing AWS ML. Without sufficient knowledge about this product, it’s difficult to work with this product.
What recommendations would you give to someone considering this product?
It has end-to-end Machine learning model development tools so companies that need to use GPUs for their projects can consider this product. Their cloud GPU services cost a little less than the entire product.
Pros
- Unique Features
- Effective Service
- Fair
- Acts with Integrity
- Role: Consultant
- Industry: Technology
- Involvement: IT Development, Integration, and Administration
Submitted Oct 2022
Ease of use; fast development
Likeliness to Recommend
Pros
- Continually Improving Product
- Reliable
- Enables Productivity
- Unique Features
Cons
- Vendor Friendly Policies
- Less Generous
Rushikesh M.
- Role: Information Technology
- Industry: Healthcare
- Involvement: IT Development, Integration, and Administration
Submitted Apr 2022
Easy, scalable, more control to developers
Likeliness to Recommend
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
