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
Sashank M.
- Role: Information Technology
- Industry: Technology
- Involvement: IT Development, Integration, and Administration
Submitted Jun 2023
Ease to use and Best in segment
Likeliness to Recommend
What differentiates AWS Machine Learning from other similar products?
Broad Range of Services: AWS offers a wide array of machine learning services, catering to different user requirements and expertise levels. Scalability and Flexibility: AWS Machine Learning provides highly scalable infrastructure, enabling users to process large volumes of data and train complex machine learning models efficiently. Integration with AWS Ecosystem: One significant advantage of AWS Machine Learning is its seamless integration with other AWS services. Flexibility in Model Development: AWS Machine Learning services support various popular machine learning frameworks, such as TensorFlow, PyTorch, and MXNet.
What is your favorite aspect of this product?
Managed Services: AWS offers fully managed services, such as Amazon SageMaker, which handle many operational aspects of machine learning. These managed services take care of infrastructure provisioning, automatic scaling, model deployment, and monitoring, Cost Optimization: AWS provides several options to optimize costs when utilizing machine learning services. Users can choose from a variety of instance types and pricing options based on their specific needs.
What do you dislike most about this product?
Complexity for Beginners: While AWS Machine Learning offers a range of services and features, the platform can be complex for users who are new to machine learning or cloud computing. Cost Management: While AWS offers cost optimization tools and options, managing costs can still be a concern, particularly for users who are new to cloud services. Vendor Lock-In: AWS Machine Learning is a part of the Amazon Web Services ecosystem, which means that using these services ties users to the AWS platform.
What recommendations would you give to someone considering this product?
Learn the Basics: Familiarize yourself with the fundamental concepts and principles of machine learning, as well as the basics of cloud computing. Understand Your Needs: Before diving into AWS Machine Learning, clearly define your goals and requirements. Leverage AWS Documentation and Resources: AWS provides comprehensive documentation, tutorials, and guides to help users get started with AWS Machine Learning. Experiment with Sample Projects: AWS offers various sample projects and examples that can serve as a starting point for your own machine learning applications.
Pros
- Helps Innovate
- Continually Improving Product
- Reliable
- Enables Productivity
Reddi Bhaskar K.
- Role: Information Technology
- Industry: Healthcare
- Involvement: IT Development, Integration, and Administration
Submitted Mar 2023
Easy to use, but a bit pricey.
Likeliness to Recommend
What differentiates AWS Machine Learning from other similar products?
All the ML related services are available in AWS
What is your favorite aspect of this product?
Labeling, rekognition of objectives and auto modeling
What do you dislike most about this product?
Live capture the images
What recommendations would you give to someone considering this product?
It's easy to implementing the ML algorithms
Pros
- Helps Innovate
- Continually Improving Product
- Reliable
- Performance Enhancing
- Role: Consultant
- Industry: Engineering
- Involvement: IT Development, Integration, and Administration
Submitted Mar 2023
The AWS Machine learning tools are remarkable.
Likeliness to Recommend
Pros
- Effective Service
- Caring
- Acts with Integrity
- Helps Innovate
