A Beginner's Guide to Natural Language Processing (NLP)

D I N I T H I
2 min readJan 14, 2020

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Natural Language Processing or simply NLP is a component of artificial intelligence. Natural Language Processing simply refers to the ability of a computer program to understand a human language as it is spoken.

Natural language is the way human communicate with each other using text and speech (voice). Text refers to the signs, emails, web pages, sms, letters, etc. We speak to each other rather than using text when communicating with each other.

There should be methods to understand the natural languages if we want to understand them.

Natural Language Processing | Definition

NLP is the interdisciplinary field of linguistics and computer science. It is the ability of computers to understand human languages.

Accordingly, NLP consists of 2 parts.

  1. Linguistics — The language, it’s syntax, meaning, formation, different phrases, parts of speech, etc.
  2. Computer science — Transforming linguistic knowledge into computer programs with the use of AI.
CS,  Linguitics  &  NLP
Image Source: https://clevertap.com/blog/natural-language-processing/

NLP plays a great role in our day to day lives. Some of the NLP based Software that are used in our daily computer interactions are:

  • Personal Assistants: Cortana, Siri, Google Assistant, Alexa
  • Spell checkers: Desktop applications (MS Word), Browsers, IDE(VS Code)
  • Auto Complete in Search Engines: Google, Bing
  • Machine translation: Google translate
Image Credits: https://deeplearninganalytics.org/wp-content/uploads/2019/04/nlp.png

NLP is divided into 3 categories.

  1. Rule based system
  2. Classical Machine Learning
  3. Deep Learning model

Benefits of NLP

  • Useful personal assistants such as Siri, Cortana..
  • Accuracy and the efficiency of documentation is improved.
  • Can make a readable summary text automatically..
  • Introducing of the Chatbots.
  • Can perform sentiment analysis easily.

Challenges of NLP

  • Abstract use of language fails NLP sometimes..
  • Semantic analysis is still a challenge.
  • The way people use the language is a challenge.

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