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Introduction to Natural Language Processing

Natural Language Processing (NLP) is a subfield of linguistics (scientific study of language) and Artificial Intelligence. It enables machines to understand and interpret human language.

NLP in our daily life:

If you have noticed Google Search is integrated with the “Search by Voice” button which enables users to search for anything by just speaking.

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At the back end, Google receives your voice recording, processes your words (Natural Language) and converts it into text, and then through text matching algorithms relevant results are displayed to you.

This is just one example, similarly our daily life is just filled with numerous applications of Natural Language Processing.

NLP based problems are not really easy. Why?

NLP based problems usually have unstructured data and when the data is in unstructured form, then data processing becomes difficult.

Unstructured data: Data which is not in proper structure and which cannot be stored in the form of row and column directly.

Video, Image, Text, Audio are examples of unstructured data.

Applications of Natural Language Processing:

  • AutoComplete feature in Emails and in Search Engines
  • Voice Recognition (Machines are able to convert Voice into Text)
  • Text to speech
  • Chatbots
  • Voice Assistants (For e.g. Alexa, Siri)
  • Sentiments Analysis (For e.g. Positive, Negative, Neutral)
  • Text Summarization (For e.g. Summarising the news into 50 words)
  • Email Spam Detection (For e.g. Spam / Not Spam)
  • Advertisements
  • Extracting information from Resume (For e.g. Named Entity Recognition)
  • And a lot more . . .

This list just goes on, as the technologies are advancing, we are becoming more and more connected with the Internet and we are producing lots of data daily over the internet. Be it your Social Media, your Product buying history, your search history, companies are just using these information to personalize your experience on their platforms.

Hence there is a growing demand in the field of NLP where engineers and scientists are engaged with unstructured data so as to make some relevant business decisions.

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