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.
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85 Likeliness to Recommend
89 Plan to Renew
75 Satisfaction of Cost Relative to Value
3
Since last award
Emotional Footprint Overview
+83 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
- Respectful
- Continually Improving Product
Emotional Footprint
How to Read
Positive
Neutral
Negative
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
Feature Ratings
Performance and Scalability
Pre-Packaged AI/ML Services
Data Ingestion
Data Pre-Processing
Feature Engineering
Model Training
Algorithm Recommendation
Data Exploration and Visualization
Ensembling
Data Labeling
Model Tuning
Vendor Capability Ratings
Ease of Data Integration
Quality of Features
Business Value Created
Breadth of Features
Ease of Implementation
Vendor Support
Product Strategy and Rate of Improvement
Ease of Customization
Usability and Intuitiveness
Ease of IT Administration
Availability and Quality of Training
AWS Machine Learning Reviews
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
Uğur Deniz Y.
- Role: Information Technology
- Industry: Technology
- Involvement: Business Leader or Manager
Submitted Jan 2023
Intuitive and successful
Likeliness to Recommend
What differentiates AWS Machine Learning from other similar products?
The AWS Machine Learning service can be integrated with other Amazon services such as Amazon S3 and Amazon Redshift, allowing data scientists to easily store, access and process data. The service also supports many open-source software such as Tensorflow and Pytorch, which gives users the flexibility to customize it to fit their specific workflows. Additionally, the service offers experienced customer support and development teams.
What is your favorite aspect of this product?
AWS facilitates data science projects by using advanced learning algorithms and data processing tools. It has an easy-to-use interface for developers and data scientists and works on Amazon's extensive cloud computing platform. AWS offers a range of tools and features to accelerate and simplify the work of data scientists. For example, the service includes tools for loading, transforming, processing, and modeling data sets. Additionally, it includes hyperparameter optimizers to optimize the performance of learning algorithms. It runs all kinds of machine learning algorithms with high performance.
What do you dislike most about this product?
It can be a bit costly. I didn't use some features I was curious about because they were expensive. There should be more updates. Limited scalability. In some cases, you may have to make additional configurations for large data sets.
What recommendations would you give to someone considering this product?
Successful, I recommend.
Pros
- Helps Innovate
- Continually Improving Product
- Reliable
- Performance Enhancing