By Abdul Rehman
In this post we are going to discuss about rapidly growing Research field which is about Language processing. We list down useful tools and previously well known developed APIs and techniques to use for processing Natural languages.
This Quora post explains it in little more depth. But here are some of the famous techniques to get you started in this field.
Tokenizer is very first and very important part of any Language processing. Because when you receive lot of text then the first step to extract information from that bunch of text is to tear apart big bunch of text into some shorter tokens, that represents some useful part of the speech.
Once you have tokens you need to recognize which part is what? First step could be to name which tokens represents some entity and name it. That’s the job of NER or Named Entity Recognizer, to recognize the entity and name that entity.
Another very famous thing to do with bunch of text representing the Natural Language is the sentiment analysis. What it do? well it could tell you about whether the provided feedback from customers are good or bad? It could also tell you by looking into trending tweets that the these tweets are about hate or love speech?
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