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Amazon Web Services (AWS)

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18,237 reviews
  • 444 profiles
  • 222 categories
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4.4
#1 in 36 categories
Grid® leader
Serving customers since
2006
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ShuffleNet V2

0 reviews

It takes an image as input and classifies the image to one of the multiple classes. The model available for deployment is pre-trained on ImageNet which comprises images of different classes. PyTorch, the PyTorch logo and any related marks are trademarks of Facebook, Inc.

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BiT-M R101x1 ImageNet-21k

0 reviews

It takes an image as input and classifies the image to one of the multiple classes. The model available for deployment is pre-trained on ImageNet-21k which comprises images of different classes. The model predicts classes including the additional class for background. TensorFlow, the TensorFlow logo and any related marks are trademarks of Google Inc.

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IaC Automated ECS Fargate Container Stack with Pre-built Jenkins CI/CD

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Deploy Infrastructure as Code - (IaC) based automated Containerized Application on AWS ECS Fargate Stack with enhanced security, CloudWatch monitoring, EFS integration, and a seamless Jenkins CI/CD pipeline for continuous delivery.

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SSD Mobilenet V2

0 reviews

It takes an image as input and returns bounding boxes for the objects in the image. The model is pre-trained on COCO 2017 which comprises images with multiple objects and the task is to identify the objects and their positions in the image. A list of the objects that the model can identify is given at the end of the page. TensorFlow, the TensorFlow logo and any related marks are trademarks of Google Inc

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BiT-M R50x1 ImageNet-21k

0 reviews

It takes an image as input and classifies the image to one of the multiple classes. The model available for deployment is pre-trained on ImageNet-21k which comprises images of different classes. The model predicts classes including the additional class for background. TensorFlow, the TensorFlow logo and any related marks are trademarks of Google Inc.

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BERT Large Cased PyTorch Hub Sentence Pair Classification

0 reviews

This is a Sentence Pair Classification model built upon a Text Embedding model from PyTorch Hub

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BERT Large Cased

0 reviews

It takes as input a pair of question-context strings, and returns a sub-string from the context as a answer to the question. The Text Embedding model which is pre-trained on English Text returns an embedding of the input pair of question-context strings. PyTorch, the PyTorch logo and any related marks are trademarks of Facebook, Inc.

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BERT Base Uncased PyTorch Hub Extractive Question Answering

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This is a Extractive Question Answering model from PyTorch Hub

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RoBERTa Large OpenAI PyTorch Hub Sentence Pair Classification

0 reviews

This is a Sentence Pair Classification model built upon a Text Embedding model from PyTorch Hub

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Amazon Web Services (AWS) Reviews

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Profile Name
Star Rating
11946
5316
729
146
96
Hammad .
H
Hammad .
🎓 | Data Science Graduate | Machine Learning | Artificial Intelligence | Data Engineering | Python | Power Bi | SQL | Excel | SPSS
07/31/2026
Validated Reviewer
Review source: G2 invite
Incentivized Review

Code Anywhere with AWS Cloud9 and Seamless AWS Integration

What I like most about AWS Cloud9 is that I can open my project from any browser and start coding right away without setting up my local environment. I also like the built-in terminal and how easily it connects with AWS services. It has made testing small changes and working on different machines much more convenient.
Sony P.
SP
Sony P.
07/31/2026
Validated Reviewer
Review source: G2 invite
Incentivized Review

Secure, Fine-Grained Access Control That Keeps AWS Productivity High

What I like most about AWS IAM is how securely it lets me manage users, roles, and permissions through fine grained access control. It integrates smoothly with other AWS services, supports multi factor authentication (MFA), and aligns well with the principle of least privilege. Overall, it helps me maintain strong security without getting in the way of productivity.
Atharva P.
AP
Atharva P.
Cloud BI Engineer at ZS | Ex-Cognizant
07/30/2026
Validated Reviewer
Verified Current User
Review source: G2 invite
Incentivized Review

Powerful, Cost-Effective S3 Sensitive Data Discovery with Amazon Macie

Amazon Macie has become an important part of our cloud security strategy by automatically discovering, classifying, and protecting sensitive data stored in Amazon S3. I particularly like its ability to identify personally identifiable information (PII), financial records, credentials, and other sensitive content without requiring custom data classification rules. The console provides intuitive dashboards, detailed findings, and risk summaries that make it easy for security teams to prioritize remediation efforts. The service integrates seamlessly with Security Hub, CloudTrail, EventBridge, IAM, and AWS Organizations to provide centralized visibility across multiple AWS accounts. Performance has been excellent when scanning large S3 environments, and scheduled discovery jobs automate ongoing compliance monitoring with minimal operational effort. Pricing is based on the amount of data evaluated, making it cost-effective for organizations that need continuous data security monitoring. Although Macie itself is not an AI service, it complements Amazon Q Security by supplying security findings that assist analysts during investigations.

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What is Amazon Web Services (AWS)?

Amazon Web Services (AWS), a subsidiary of Amazon, is a leading cloud computing platform that provides a wide range of on-demand services such as computing power, data storage, databases, networking, and artificial intelligence tools. It enables businesses to build, deploy, and scale applications without investing in physical infrastructure, using a flexible pay-as-you-go pricing model. With a global network of data centers, AWS supports organizations of all sizes—from startups to large enterprises—by offering reliable, secure, and highly scalable solutions for modern digital operations.

Details

Year Founded
2006
Ownership
NASDAQ: AMZN
Website
aws.amazon.com