Introduction to Natural Language Processing.

Introduction to Natural Language Processing.

NLP for the absolute beginner

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Here is my Little Introduction to Natural Language Processing which I learn in my academics. I am sure it helps you understand the basics of NLP with some real-world examples.

Natural Language Processing focuses on enabling machines to use language which humans use in daily lives to mimic human conservations. NLP is a Sub-Field of AI that is focused on enabling machines to understand and process human conservations.

Think for a moment as to how we listen and talk; how our brain processes language. Now imagine if computers need to do that. How will they understand what we say in our language? This blog is all about demystifying the NLP domain and understanding how it works.

HOW HUMAN COMMUNICATES

Humans communicate through language. We might use different languages or dialects or slang but we need some sequence of letters and symbols to communicate, right?

When we communicate, our brain listens to information and then tries to interpret it in the set of symbols or language which we know. We are also great at parallelly listening to various conservation or texting our friends while listening to our parents sounds familiar?

So, if we look at the above example, the brain process both texting our friends and listening to our parents and prioritizes the one where our interest lies more, which is listening to our parents in this case.

The Science of listening is also very interesting. As a person speaks, the sound travels from the speaker's mouth to the listener's ear and is converted into a neuron impulse. It is then interpreted in the brain and the listener understands it.

Or asks for further clarification if the message is not clear. This is how human conservation is processed.

HOW COMPUTER COMMUNICATE

We know that computers work on binary and everything which is coded into a computing language gets translated into machine language. What if computers can understand human language and act upon it?

imagine if you could say or write - print Gaurav - rather than typing as a syntax - print("Gaurav") - and it automatically understands what you mean without any complicated codes.

NLP deals with the idea of having computers understand human language without expert programming. How amazing would that be?

COMPONENTS OF NLP

  1. Morphological analysis
  2. Lexical analysis
  3. Syntactic analysis
  4. Semantic analysis
  5. Disclosure Integration
  6. Pragmatic analysis

APPLICATIONS OF NLP

• Automatic Text Summarization: We are constantly consuming information and to be able to extract the key message from a large text is of value. Automatic summarization can be used to summarize news, articles, or content.

• Sentiment and Emotion Analysis: We can use sentiment analysis to predict the general emotion of a text. Let us say we want to know how the general public is feeling about a political figure or celebrity. We can use this technique to go through all the social media posts and articles/blogs to see what is the sentiment of the public.

• Text Classification: Text classification can help in organizing information and ensuring categorizing of data sets. For e.g, an application of text categorization is spam filtering in the email based on certain keywords.

• Virtual Assistants: We have seen that Google Assistants, Cortana, Siri, Alexa, etc., have become an important part of our life. These assistants can detect our voices and give personalized responses to our queries.

This is the very basic Introduction to NLP

Thank You!

I am Gaurav 14 y/o Python Developer and I love to contribute to Open-Source on GitHub, Currently Learning Machine Learning. You can follow me for more content on Python and Machine Learning.

 
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