Overview
Product Information on Amazon SageMaker
Updated 7th June 2026
What is Amazon SageMaker?
Amazon SageMaker Pricing
Overall experience with Amazon SageMaker
Data Analyst
Gov't/PS/ED <5,000 Employees, EducationFAVORABLE
“Efficient end-to-end ML workflows with integrated AWS tools”
SageMaker is a strong platform for building, training and deploying machine learning models at scale. The biggest advantages are its seamless integration with the AWS ecosystem, managed infrastructure and ability to handle end-to-end ML workflows efficiently. Features like SageMaker Studio, built-in algorithms, automated model training and scalable deployment endpoints have significantly reduced operational overhead for our team.
IT Manager
<50M USD, BankingCRITICAL
“Extensive Machine Learning Options Offset by High Cost and Complex Navigation”
i am able to navigate and figure out how to spin up notebooks etc, but it takes time
About Company
Company Description
Amazon Web Services (AWS), established in 2006, is focused on providing essential infrastructure services to businesses globally in the form of cloud computing. The key advantage offered through cloud computing, particularly via AWS, is its capacity to shift fixed infrastructure expenses into flexible costs. Businesses have been able to forgo extensive planning and procurement of servers and other Information Technology (IT) resources, owing to AWS. AWS seeks to provide businesses with prompt and cost-effective access to resources using Amazon's expertise and economies of scale, as and when their business requires. Currently, AWS offers a robust, scalable, economic infrastructure platform on the cloud powering an extensive array of businesses worldwide. It operates across numerous industries with data center locations in various parts of the globe including U.S., Europe, Singapore, and Japan.
Company Details
Company type
Public
Year Founded
2006
Head office location
Seattle, United States
Number of employees
10001+
Website
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- Data AnalystGov't/PS/EdEducationReview Source
Efficient end-to-end ML workflows with integrated AWS tools
SageMaker is a strong platform for building, training and deploying machine learning models at scale. The biggest advantages are its seamless integration with the AWS ecosystem, managed infrastructure and ability to handle end-to-end ML workflows efficiently. Features like SageMaker Studio, built-in algorithms, automated model training and scalable deployment endpoints have significantly reduced operational overhead for our team. - IT SECURITY & RISK MANAGEMENT ASSOCIATE10B+ USDBankingReview Source
faily easy to use ML software
overall experience has been good, fairly easy to learn and advance into higher business purpose evolution - Software Developer50M-1B USDInsurance (except health)Review Source
Sage maker for every ml use case
Sagemaker makes it easy to work with the ML models of your choice and you upload any numbers of models. - DIRECTOR OF FINANCE10B+ USDInsurance (except health)Review Source
Infrastructure Enables Flexible Cloud Migration for Volatile End-User Codebases
sagemaker gave us the infrastructure at that point in time to move end-user managed codebase with volatile workload to the cloud - Director of Data and Analytics50M-1B USDBankingReview Source
Concerns Raised Over Data Size Limits and Unclear Future Implementation Strategy
Looking for more improvements. Not clear about future strategy to implement the product
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