Amazon Comprehend vs. Keras

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amazon Comprehend
Score 7.4 out of 10
N/A
Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to find insights and relationships in text. Amazon Comprehend uses machine learning to help uncover insights and relationships in unstructured data. The service identifies the language of the text; extracts key phrases, places, people, brands, or events; understands how positive or negative the text is; analyzes text using tokenization and parts of speech; and automatically organizes a collection of text…
$0
per unit
Keras
Score 7.9 out of 10
N/A
Keras is a Python deep learning libraryN/A
Pricing
Amazon ComprehendKeras
Editions & Modules
Syntax Analysis
$0.00005
per unit
Key Phrase Extraction
$0.0001
per unit
Sentiment Analysis
$0.0001
per unit
Entity Recognition
$0.0001
per unit
Language Detection
$0.0001
per unit
Pll Detection
$0.0001
per unit
Event Detection Per Event Type
$0.003
per unit
No answers on this topic
Offerings
Pricing Offerings
Amazon ComprehendKeras
Free Trial
YesNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Amazon ComprehendKeras
Top Pros

No answers on this topic

Top Cons
Best Alternatives
Amazon ComprehendKeras
Small Businesses
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
Medium-sized Companies
Posit
Posit
Score 9.3 out of 10
Posit
Posit
Score 9.3 out of 10
Enterprises
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Amazon ComprehendKeras
Likelihood to Recommend
10.0
(1 ratings)
8.1
(6 ratings)
Usability
-
(0 ratings)
7.7
(2 ratings)
Support Rating
-
(0 ratings)
8.2
(2 ratings)
User Testimonials
Amazon ComprehendKeras
Likelihood to Recommend
Amazon AWS
Specifically, it starts processing millions of documents in minutes by leveraging the power of machine learning without having trained models from scratch. If any of the content contains personally identifiable information not only can Amazon Comprehend locate it but it will also redact or mask it. Using NLP techniques Amazon Comprehend goes well beyond keyword search or rules-based tagging to accurately classify documents. For my task or development, I cannot find any difficulties with Amazon Comprehend.
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Open Source
Keras is quite perfect, if the aim is to build the standard Deep Learning model, and materialize it to serve the real business use case, while it is not suitable if the purpose is for research and a lot of non-standard try out and customization are required, in that case either directly goes to low level TensorFlow API or Pytorch
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Pros
Amazon AWS
  • Amazon Comprehend identifies the language of the text and extracts Key-phrases, places, people, brands or events.
  • It can build a custom set of entities or text classification models that are tailored uniquely to the organisation's need
  • Amazon Comprehend's medical can be used to identify medical conditions, medications, dosages, strength and frequencies from sources like doctor's notes, clinical trial reports and patient health records. This service is very good and with well an accuracy or confidence score.
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Open Source
  • One of the reason to use Keras is that it is easy to use. Implementing neural network is very easy in this, with just one line of code we can add one layer in the neural network with all it's configurations.
  • It provides lot of inbuilt thing like cov2d, conv2D, maxPooling layers. So it makes fast development as you don't need to write everything on your own. It comes with lot of data processing libraries in it like one hot encoder which also makes your development easy and fast.
  • It also provides functionality to develop models on mobile device.
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Cons
Amazon AWS
  • It will be great if Amazon Comprehend provide support specifically for litigation or related text documents to extract insights from it.
  • For REST API support using JAVA SDK, it will be great for developers if they provide support for testing without any credentials or account details.
  • Setting up for REST API integration can be as simple as possible.
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Open Source
  • As it is a kind of wrapper library it won't allow you to modify everything of its backend
  • Unlike other deep learning libraries, it lacks a pre-defined trained model to use
  • Errors thrown are not always very useful for debugging. Sometimes it is difficult to know the root cause just with the logs
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Usability
Amazon AWS
No answers on this topic
Open Source
I am giving this rating depending on my experience so far with Keras, I didn't face any issue far. I would like to recommend it to the new developers.
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Support Rating
Amazon AWS
No answers on this topic
Open Source
Keras have really good support along with the strong community over the internet. So in case you stuck, It won't so hard to get out from it.
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Alternatives Considered
Amazon AWS
For natural language processing tasks or techniques, there are many service providers out there in the market such as Azure Cloud Services, IBM Watson and Google Cloud Platform (GCP), but compared with them, Amazon Comprehend is the best service provider in contents of accuracy, speed of processing multilingual text, supporting SDK for most of the languages and well documented.
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Open Source
Keras is good to develop deep learning models. As compared to TensorFlow, it's easy to write code in Keras. You have more power with TensorFlow but also have a high error rate because you have to configure everything by your own. And as compared to MATLAB, I will always prefer Keras as it is easy and powerful as well.
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Return on Investment
Amazon AWS
  • It supports better and accurately as compared with our existing or old implementations. So, we fulfil our needs as per clients' requirements and it will help to grow or improve client satisfaction.
  • For these specific requirements, we do not require any machine learning engineers or related professionals to hire in our organisation.
  • None of any negative sides can be affected our business or distract existing clients.
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Open Source
  • Easy and faster way to develop neural network.
  • It would be much better if it is available in Java.
  • It doesn't allow you to modify the internal things.
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ScreenShots