Build NLP applications like sentiment analysis, word classification, NER, text extraction and more with AWS ML and Boto3

Natural Language processing is one of the domain in Artificial Intelligence, that helps machine understand, interpret, manipulate and respond to human language.

We all are seeing more then thousands of Natural language applications such as signboard, menus, email, SMS, webpage, chats, reviews and so much more on daily life. NLP is everywhere. Natural language is not just about what we see, it also includes human speech as well. There are endless example of natural language application that can used in many use cases such as business and job opportunity.

NLP process the natural language by combining statistical, machine learning, and deep learning models and derive meaning from it.

In this course, you will learn about Natural language processing and it’s application with the help of AWS Comprehend, Translate, Transcribe and Polly.

• What is AWS Comprehend ?

  Amazon Comprehend is a natural-language processing (NLP) service that uses machine learning to identify the language of the text, extract key phrases, places, people, brands, or events, understand sentiment about products or services, and identify the main topics from a library of documents.

  
  

• What is AWS Translate ?

  Amazon Translate is a neural machine translation service that enables to translate between a source language and a target language .

  
  

• What is AWS Transcribe ?

  AWS transcribe service that helps to add speech to text functionality into the applications.

  
  

• What is AWS Polly ?

  Amazon Textract is a machine learning (ML) service that transform text into human voice.

  
  

Aprenda PNL – Procesamiento del lenguaje natural con AWS y Python

Build NLP applications like sentiment analysis, word classification, NER, text extraction and more with AWS ML and Boto3″

Este curso es GRATIS

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Este curso se encuentra disponible de manera gratuita sin necesidad de ningún cupón, a través de la opción “GRATIS”.

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