About Natural Language Processing

Natural Language Processing or NLP for short is a field of computer science, artificial intelligence (AI) and computational linguistics concerned with the interactions between computers and human natural language.  It’s a relatively new field and a “hot” area in technology today. Read some more about it from our Data Science instructor Lesley Cordero.

What is the significance of Natural Language Processing?

NLP applications can actually be very useful and informative.  The area has a lot of growing to do which makes it all that more exciting right now.  It’s a core part of data mining in education, medical sciences, and so many other fields. Think about how much data out there is in text form – facebook posts, tweets, medical evaluations, essays, articles, google searches, and more – Natural Language Processing can be used for all.

What are the obstacles for the computer to process natural language?

Put shortly, ambiguity is the core obstacle of natural language processing. Unlike code where there’s a specific structure which you must abide by, the rules of grammar and language are much more open to interpretation. The same text can be interpreted very differently depending on semantics, tone, culture (dialect) and other variables, so it’s hard to generalize.

And that’s just assuming you use the same language. There are hundreds of languages in the world, making the problem of processing natural languages much tougher.

So again, ambiguity is the biggest challenge here.

How can machine learning or deep learning most likely advance natural language processing in the future?

Firstly, I want to clarify that lots of Natural Language Processing algorithms are based on machine learning techniques. So by no means, can you really think of them as completely separate fields. With that said, the intersection of deep learning and natural language processing is actually super interesting. Word2Vecs are actually a very hot topic right now and provide an in-depth understanding of how the two (DL & NLP) influence each other.

I recommend the following readings if you want to learn more!

  1. Implementing a CNN for Text Classification
  2. Deep or Shallow: NLP is Breaking Out
  3. Attention & Memory in Deep Learning & NLP



Pin on PinterestShare on FacebookTweet about this on TwitterShare on LinkedInShare on RedditShare on TumblrEmail this to someone
Thanks for the comment
No Comments

Other Suggested Reads

  • Computational Science 101

    Read tips from our Data Science instructor, Lesley Cordero, regarding how to get started in computational science. How does one get started in computational science? Assuming you have the proper bac...
  • Women Better Coders Than Men? (Kick More Ass With Scholarships)

    In the 1940's more than half of programmers were women, yet, that proportion hovers around 25% today.  Many studies find that the actual percentage of women is more like 10% - 20%.  When big tech co...
  • A Banker’s Guide To Winning His First Hackathon

    Hackathons aren't all about  glasses, geeks, pocket-protectors, and Red Bull, although such stereotypes may turn off many from entering them... This may have been the case with Dan Griffin, a sel...