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Amazon Web Services (AWS)

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18,252 reviews
  • 447 profiles
  • 222 categories
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4.4
#1 in 34 categories
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ELECTRA-Base++

0 reviews

It takes a text string as input and classifies the input text as either a positive or negative movie review. The Text Embedding model which is pre-trained on WikiPedia and BookCorpus returns an embedding of the input text. TensorFlow, the TensorFlow logo and any related marks are trademarks of Google Inc.

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MobileNet V1 0.25 224

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. 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 Uncased

0 reviews

It takes a pair of sentences as input and classifies the input pair to 'entailment' or 'no-entailment'. The class label entailment implies the second sentence entails the first sentence, and the no-entailment implies it does not. The Text Embedding model which is pre-trained on English Text returns an embedding of the input pair of sentences. The model available for deployment is created by attaching a binary classification layer to the output of the Text Embedding model, and then fine-tuning the entire model on [QNLI](https://rajpurkar.github.io/SQuAD-explorer/ ) dataset. PyTorch, the PyTorch logo and any related marks are trademarks of Facebook, Inc.

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BERT Base MEDLINE/PubMed

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It takes a text string as input and classifies the input text as either a positive or negative movie review. The Text Embedding model which is pre-trained on MEDLINE/PubMed returns an embedding of the input text. TensorFlow, the TensorFlow logo and any related marks are trademarks of Google Inc.

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MobileNet V1 0.50 128

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. 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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MobileNet 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. 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 Whole Word Masking SQuAD

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 Wikipedia and BooksCorpus

0 reviews

It takes a pair of sentences as input and classifies the input pair to 'entailment' or 'no-entailment'. The class label entailment implies the second sentence entails the first sentence, and the no-entailment implies it does not. The Text Embedding model which is pre-trained on WikiPedia and BookCorpus returns an embedding of the input pair of sentences. TensorFlow, the TensorFlow logo and any related marks are trademarks of Google Inc.

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EfficientNet B7

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. 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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Amazon Web Services (AWS) Reviews

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Profile Name
Star Rating
11953
5318
731
146
96
Moniba S.
MS
Moniba S.
Enterprise Cloud & AI Leader |Account Management & New Logo Acquisition |$5M+ ARR Closed |FinOps · Security · AWS · Azure · GCP · GCC |Helping CEOs/CTOs Optimize IT Spend |Reducing LLM Cost |AWS Certified AI Practitioner
09/29/2026
Validated Reviewer
Review source: Organic

Powerful Data Handler with Room for Visualization Improvement

I like that Amazon Quick handles massive datasets without slowing down, which is really important for my work. Its embedded feature also works really well, making it more convenient to use.
SK
Saurav K.
09/27/2026
Validated Reviewer
Review source: G2 invite

Easy Setup and Management with Flexible, Scalable AWS Integration

I like how easy Amazon Connect is to set up and manage. It brings customer interactions into one place and offers good flexibility, scalability and integration with other AWS services.
tejashri p.
TP
tejashri p.
Data Scientist with 3.5 years of experience in end to end Machine learning, NLP, Deep Learning, Predictive Analytics, Python, SQL,, Spark, AWS, Azure, Generative AI
09/26/2026
Validated Reviewer
Verified Current User
Review source: Organic
Translated Using AI

Easy to access for beginners

As we can easily create virtual server instances also keeping compute power, memory at optimum. It's pay as you go feature helps you manage resources mindfully. It becomes easier for me to connect it to redis or S3 storage for my infrastructure needs. It is scalable service.

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Seattle, WA

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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