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Natural Language Processing Using Python

What is NLP?

NLP stands for Natural Language Processing. To put it in a simple way, NLP is a way of developing applications which can understand human language. Millions of Gigabytes of data is being generated every day and there is a high demand to understand this data in a simpler way. We have different analytical methods to fetch insights from numerical data, and NLP comes into the picture when we are dealing with textual data.

What are the applications of NLP?

NLP is being used heavily in the following domain:-
1. Search Engines – Be it Google or Bing, we write a query and rely on the NLP part of the algorithm to fetch us the best results.
2. Speech Engines – Almost all mobile phones come with an inbuilt speech engine which translates your voice feed into a query and gets you the search results. Example – Siri
3. Social Media – Have you ever wondered how you are receiving relevant ads in your social media feed? Well, that is NLP, decoding your interest and pushing relevant ads on your feed
4. Survey Analysis – You must have filled some surveys, and there are billions of survey copies in the digital world, you need to go through every survey answer to get a gist of customer sentiments, but going through millions of copies is quite cumbersome. So, what do you do? You build an NLP model, feed the content and boom..It’s done.
5. Artificial Intelligence Chat Bot – This is one important application of NLP, where you chat with a bot and it gets what you ask for
6. Spam filters – For every relevant email, there are at least 2 spam emails, but you never worry about it because you never got to see one. All those spam filters are powered by NLP

What are we going to learn in this post?

We will use Python to understand the basics of NLP, regular expression and few algorithms. So, be with us for another 30-40 minutes to understand Natural Language Processing using Python.

Before starting NLP, Please go through Regular Expression.






About TheDataMonkMaster

I am the Co-Founder of The Data Monk. I have a total of 4+ years of analytics experience with 3+ years at Mu Sigma and 1 year at OYO. I am an active trader and a logically sarcastic idiot :)

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