NLP Applications

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Table of Contents
What is Natural Language Processing?
Which Are the Major Categories of NLP Technology?

Why is NLP so important?
What are examples of NLP applications in
business?
Whats the difference between NLP and Text
Analytics?
Neural Networks
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What is Natural Language Processing?

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Natural Language Processing (NLP) is an
artificial intelligence (AI) technology that
allows a machine to recognize and decipher the
nuances of human language. It organizes
unstructured data by analyzing it for relevancy,
differences in spellings, correlation, and
semantic meaning. It tries to understand
different lexicons, grammatical syntaxes, and the
relation between words and phrases, just as a
human does. And remembers it. NLP is used
successfully today in speech pattern recognition,
weather forecasting, healthcare applications, and
classifying handwritten documents. There are in
fact so many NLP applications in business we
ourselves use daily that we dont even realise
how ubiquitous the technology really is. Smart
assistants like Siri and Alexa, our car
navigation system that tells us the fastest
route, our favourite OTT streaming channel that
suggests which movies wed like to watch,
autocomplete predictive texts on our phones,
translation apps - they are all examples of how
NLP has become an integral part of our lives.
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Which Are the Major Categories of NLP Technology?
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Why is NLP so important?
The interest companies are showing in embracing
NLP-based solutions is gaining momentum fast.
According to an industry report, the forecasted
global NLP market size is set to be US 35.1
Billion by 2026. The rise is in almost all
verticals including healthcare, credit card and
insurance fraud investigations, and text
analytics for customer sentiment analysis. NLP is
also generating a great deal of interest in
intelligent document analysis in aviation, drone
control, robotics, and heavy machinery
industries. Companies are realizing that
AI-powered solutions are only going to get bigger
and better. And if you dont explore the
technology now, doesnt mean your competitors
wont.
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What are examples of NLP applications in business?
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What are the challenges in managing consumer
insights data?
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Whats the difference between NLP and Text
Analytics?
NLP technology understands, interprets, and
classifies a companys raw, unstructured big data
collected from different sources like customer
reviews, social media listening, employee forums,
etc. Text analytics takes this now organized
data, and drives it through machine learning (ML)
algorithms to gain insights from it. This is how
text analytics helps a company discover business
intelligence for prescriptive and predictive
analytics within minutes. But before an ML model
can begin work on a set of data for your
industry, and you in particular, it has to be
trained. And in order to be trained, it needs to
have an annotated corpus of data that is
representative of the text that will be
eventually analyzed. Without NLP, there is
precious little that can be done to train the
machine model.
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