Reports‌what is natural language processing EN
Created by Bernard Huang
Last edited
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‌ machinelearningmastery.com/natural-language-processing/#1 desktop
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‌ www.sas.com/en_us/insights/analytics/what-is-natural-language-processing-nlp.html#2 desktop
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‌ en.wikipedia.org/wiki/Natural_language_processing#3 desktop
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‌ en.m.wikipedia.org/wiki/Natural_language_processing#3 mobile
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‌ www.ibm.com/cloud/learn/natural-language-processing#4 desktop
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‌ searchenterpriseai.techtarget.com/definition/natural-language-processing-NLP#5 desktop
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‌ www.google.com/amp/s/searchenterpriseai.techtarget.com/definition/natural-language-processing-NLP%3Famp=1#5 mobile
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‌ becominghuman.ai/a-simple-introduction-to-natural-language-processing-ea66a1747b32#6 desktop
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‌ towardsdatascience.com/your-guide-to-natural-language-processing-nlp-48ea2511f6e1#7 desktop
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‌ monkeylearn.com/blog/what-is-natural-language-processing/#7 mobile
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‌ algorithmia.com/blog/introduction-natural-language-processing-nlp#8 desktop
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‌ www.cio.com/article/3258837/natural-language-processing-nlp-explained.html#9 desktop
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‌ www.google.com/amp/s/www.cio.com/article/3258837/natural-language-processing-nlp-explained.amp.html#9 mobile
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‌ www.tableau.com/learn/articles/natural-language-processing-examples#10 mobile
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‌ monkeylearn.com/natural-language-processing/#11 desktop
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‌ www.wonderflow.ai/blog/natural-language-processing-examples#11 mobile
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‌ www.linguamatics.com/what-text-mining-text-analytics-and-natural-language-processing#12 mobile
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‌ www.expert.ai/blog/natural-language-processing/#13 mobile
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‌ enterprisersproject.com/article/2019/9/natural-language-processing-nlp-explained-plain-english#14 mobile
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‌ datascience.foundation/sciencewhitepaper/natural-language-processing-nlp-simplified-a-step-by-step-guide#15 mobile
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‌ www.google.com/amp/s/healthitanalytics.com/features/amp/what-is-the-role-of-natural-language-processing-in-healthcare#16 mobile
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‌ builtin.com/data-science/easy-introduction-natural-language-processing#18 desktop
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‌ www.deeplearning.ai/program/natural-language-processing-specialization/#18 mobile
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‌ www.coursera.org/specializations/natural-language-processing#19 desktop
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‌ www.twilio.com/docs/glossary/what-natural-language-processing-nlp#19 mobile
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‌ www.google.com/amp/s/morethandigital.info/en/nlp-explained-what-is-natural-language-processing/amp/#20 mobile
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‌ www.interactions.com/natural-language-processing/#21 desktop
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‌ morethandigital.info/en/nlp-explained-what-is-natural-language-processing/#22 desktop
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‌ www.tutorialspoint.com/artificial_intelligence/artificial_intelligence_natural_language_processing.htm#22 mobile
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‌ healthitanalytics.com/features/what-is-the-role-of-natural-language-processing-in-healthcare#23 desktop
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‌ www.foreseemed.com/natural-language-processing-in-healthcare#23 mobile
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‌ www.constructdigital.com/insight/what-is-natural-language-processing#24 mobile
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‌ www.bold360.com/learn/what-is-natural-language-processing#25 mobile
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‌ www.techopedia.com/definition/653/natural-language-processing-nlp#26 desktop
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‌ www.investopedia.com/terms/n/natural-language-processing-nlp.asp#27 mobile
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‌ www.google.com/amp/s/blog.aureusanalytics.com/blog/5-natural-language-processing-techniques-for-extracting-information%3Fhs_amp=true#29 mobile
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natural language processing
‌ H
Typical: 6–18 (4)
‌
nlp
‌ H
Typical: 11–31 (2)
‌
machine learning
‌ H
Typical: 2–6
‌
artificial intelligence
Typical: 1–3
‌
semantic
Typical: 2–4
‌
human language
Typical: 3–7
‌
algorithms
Typical: 2–6
‌
sentiment analysis
Typical: 2–4
‌
english
Typical: 1–3
‌
chatbots
Typical: 2–4
‌
python
Typical: 2–4
‌
deep learning
Typical: 2–6
‌
machine translation
Typical: 1–3
‌
social media
Typical: 1–3
‌
summarization
Typical: 1–2
‌
computer science
Typical: 1–2
‌
computational linguistics
Typical: 1–2
‌
speech recognition
Typical: 1–2
‌
alexa
Typical: 1–2
‌
unstructured data
Typical: 1–3
‌
natural language understanding
Typical: 1–3
‌
siri
Typical: 1–2
‌
syntax
Typical: 1–2
‌
search engines
Typical: 1–3
‌
neural networks
Typical: 1–3
‌
real-world
Typical: 1–2
‌
natural language generation
Typical: 1–3
‌
tokenization
Typical: 1–2
‌
stemming
Typical: 1–3
‌
part-of-speech tagging
Typical: 1–2
‌
tutorials
Typical: 1–3
‌
parsing
Typical: 1–2
‌
amazon
Typical: 1–3
‌
lemmatization
Typical: 1–2
‌
named entity recognition
Typical: 1–3
‌
nlu
Typical: 1–3
‌
disambiguation
Typical: 1–2
‌
machine learning methods
Typical: 1–2
‌
semantic analysis
Typical: 1–2
‌
data sets
Typical: 1–2
‌
topic modeling
Typical: 1–2
‌
use cases
Typical: 1–3
‌
nlp systems
Typical: 1–2
‌
virtual assistants
Typical: 1–2
‌
text summarization
Typical: 1–2
‌
processing tasks
Typical: 1–2
‌
nlp algorithms
Typical: 1–2
‌
healthcare
Typical: 2–6
‌
nltk
Typical: 2–4
‌
text data
Typical: 1–2
‌
statistical methods
Typical: 1–2
‌
big data
Typical: 2–6
‌
automation
Typical: 1–2
‌
nlp models
Typical: 1–2
‌
nlg
Typical: 1–3
‌
nlp applications
Typical: 1–3
‌
language models
Typical: 1–3
‌
nlp tasks
Typical: 1–3
‌
question answering
Typical: 1–3
‌
nlp technology
Typical: 1–2
‌
segmentation
Typical: 1–3
‌
ibm
Typical: 1–3
‌
python library
Typical: 1–2
‌
data scientists
Typical: 1–2
‌
branch of artificial intelligence
Typical: 1–2

natural language processing

natural-language-processing, nat­ur­al lan­guage pro­cessing, natural_language_processing
Importance: 10/10
Heading presence: ‌ High
Typical uses: 6–18
Current uses: 4

nlp

nlps
Importance: 10/10
Heading presence: ‌ High
Typical uses: 11–31
Current uses: 2

machine learning

machine-learning, machine_learning
Importance: 10/10
Heading presence: ‌ Moderate
Typical uses: 2–6
Current uses: -

artificial intelligence

Importance: 9/10
Typical uses: 1–3
Current uses: -

semantic

semantics
Importance: 9/10
Typical uses: 2–4
Current uses: -

human language

human languages, hu­man lan­guage, human-language
Importance: 8/10
Typical uses: 3–7
Current uses: -

algorithms

algorithm
Importance: 8/10
Typical uses: 2–6
Current uses: -

sentiment analysis

Importance: 7/10
Typical uses: 2–4
Current uses: -

english

Importance: 7/10
Typical uses: 1–3
Current uses: -

chatbots

chatbot, chat bots
Importance: 7/10
Typical uses: 2–4
Current uses: -

python

Importance: 7/10
Typical uses: 2–4
Current uses: -

deep learning

deeplearning, deep-learning
Importance: 6/10
Typical uses: 2–6
Current uses: -

machine translation

Importance: 6/10
Typical uses: 1–3
Current uses: -

social media

Importance: 6/10
Typical uses: 1–3
Current uses: -

summarization

Importance: 5/10
Typical uses: 1–2
Current uses: -

computer science

Importance: 5/10
Typical uses: 1–2
Current uses: -

computational linguistics

Importance: 5/10
Typical uses: 1–2
Current uses: -

speech recognition

Importance: 5/10
Typical uses: 1–2
Current uses: -

alexa

Importance: 5/10
Typical uses: 1–2
Current uses: -

unstructured data

Importance: 5/10
Typical uses: 1–3
Current uses: -

natural language understanding

Importance: 5/10
Typical uses: 1–3
Current uses: -

siri

Importance: 5/10
Typical uses: 1–2
Current uses: -

syntax

syntaxes
Importance: 5/10
Typical uses: 1–2
Current uses: -

search engines

search engine
Importance: 5/10
Typical uses: 1–3
Current uses: -

neural networks

neural network
Importance: 5/10
Typical uses: 1–3
Current uses: -

real-world

real world
Importance: 5/10
Typical uses: 1–2
Current uses: -

natural language generation

natural-language generation
Importance: 4/10
Typical uses: 1–3
Current uses: -

tokenization

tokenizations
Importance: 4/10
Typical uses: 1–2
Current uses: -

stemming

Importance: 4/10
Typical uses: 1–3
Current uses: -

part-of-speech tagging

part of speech tagging, part-of-speech-tagging
Importance: 4/10
Typical uses: 1–2
Current uses: -

tutorials

tutorial
Importance: 4/10
Typical uses: 1–3
Current uses: -

parsing

Importance: 4/10
Typical uses: 1–2
Current uses: -

amazon

Importance: 4/10
Typical uses: 1–3
Current uses: -

lemmatization

Importance: 4/10
Typical uses: 1–2
Current uses: -

named entity recognition

Importance: 4/10
Typical uses: 1–3
Current uses: -

nlu

Importance: 4/10
Typical uses: 1–3
Current uses: -

disambiguation

Importance: 4/10
Typical uses: 1–2
Current uses: -

machine learning methods

Importance: 3/10
Typical uses: 1–2
Current uses: -

semantic analysis

Importance: 3/10
Typical uses: 1–2
Current uses: -

data sets

datasets, dataset, data set
Importance: 3/10
Typical uses: 1–2
Current uses: -

topic modeling

Importance: 3/10
Typical uses: 1–2
Current uses: -

use cases

use case
Importance: 3/10
Typical uses: 1–3
Current uses: -

nlp systems

nlp system
Importance: 3/10
Typical uses: 1–2
Current uses: -

virtual assistants

virtual assistant
Importance: 3/10
Typical uses: 1–2
Current uses: -

text summarization

Importance: 3/10
Typical uses: 1–2
Current uses: -

processing tasks

processing task
Importance: 3/10
Typical uses: 1–2
Current uses: -

nlp algorithms

nlp algorithm
Importance: 3/10
Typical uses: 1–2
Current uses: -

healthcare

health care
Importance: 3/10
Typical uses: 2–6
Current uses: -

nltk

Importance: 3/10
Typical uses: 2–4
Current uses: -

text data

Importance: 3/10
Typical uses: 1–2
Current uses: -

statistical methods

Importance: 3/10
Typical uses: 1–2
Current uses: -

big data

Importance: 3/10
Typical uses: 2–6
Current uses: -

automation

Importance: 3/10
Typical uses: 1–2
Current uses: -

nlp models

nlp model
Importance: 3/10
Typical uses: 1–2
Current uses: -

nlg

Importance: 3/10
Typical uses: 1–3
Current uses: -

nlp applications

nlp application
Importance: 3/10
Typical uses: 1–3
Current uses: -

language models

language model
Importance: 3/10
Typical uses: 1–3
Current uses: -

nlp tasks

nlp task
Importance: 3/10
Typical uses: 1–3
Current uses: -

question answering

question-answering
Importance: 3/10
Typical uses: 1–3
Current uses: -

nlp technology

Importance: 3/10
Typical uses: 1–2
Current uses: -

segmentation

Importance: 3/10
Typical uses: 1–3
Current uses: -

ibm

Importance: 3/10
Typical uses: 1–3
Current uses: -

python library

python libraries
Importance: 3/10
Typical uses: 1–2
Current uses: -

data scientists

data scientist, datascientist
Importance: 3/10
Typical uses: 1–2
Current uses: -

branch of artificial intelligence

Importance: 3/10
Typical uses: 1–2
Current uses: -