A guide to natural language processing

A Beginners Guide to NLP(Natural Language Processing)

A Beginners Guide to NLP

Natural Language Processing is considered to be an amazing field which is related to text and speech recognition. It is a vehement area of artificial intelligence and computer science, which deals with the interaction between human languages and that of computers. This is the context of how to program computers effectively so that they can process and analyze a lot of natural language data formats. It is a notion that for data scientists, Natural Processing Language (NLP) is the magnum opus.

But what actually is NLP?

To explain in a simpler manner, NLP is the development of services or applications, which can understand the human language. The practical examples of NLP include speech translation, speech recognition, understanding synonyms of the matching words, understanding of the complete sentences, and also generation of sentences and paragraphs which are grammatically correct. NLP can do much more than this.

NLP based programming is executed in:

  1. Spam filtering: NLP judges the spam by understanding the deep meaning of the content, which is present in the mail. For example, the Google spam filter
  2. Search engines: The most used search engines like Yahoo and Google where the Google search engine shows you the technology-related results since it knows that you are a technician.
  3. Speech engine: The best example is Apple’s Siri and Amazons
  4. Social network push: Consider Facebook’s News Feed. If you are interested in natural language processing, the News Feed algorithm will bombard you, as opposed to your liking, with ads and posts.

NLP library

Below are the mentioned open source natural language processing libraries (NLPs):

  1. Apache OpenNLP
  2. Gate NLP library
  3. Natural language toolkit (NLTK)
  4. Stanford NLP suite

Natural language toolkit (NLTK) is considered to be the well-sought Natural Language Processing Library (NLP) that has been written in Python which also has vehement community support for it. It has also been made a notion that NLTK is very easy to use and is the simplest natural language processing (NLP) library.

How to install NLTK?

If you use Linux/Mac/Windows, you can install NLTK by using pip: All you have to do is open the python terminal and then import the NLTK in order to check if NLTK has been installed correctly or not and if all is going well, it means that you have installed NLTK library successfully. If you are going to install NLTK for the first time, all you have to do is install the NLTK extension package by running the below code:

import nltk


Then, the NLTK download window will pop up where you can choose the packages which needs to be installed, accordingly.

When it comes to data science, in this context, there can be many data science tools which are currently available like:

  1. Hashing Vectorization
  2. Lemmatization
  3. Parsing
  4. Stemming

NLP is a complicated and large area and it also constitutes to be an area of a great amount of study. There are said to be many useful tools that are very beneficial in interpreting and utilizing the words extensively.