Humans are social animals. So they interact. It is their innate tendency to. They use several media to express themselves. Humans have changed the ways of communication over time. From fire signals in the pre-historic times to SMS lingo that we widely use today. They’ve come up with languages that they understand and reciprocate with.
Now, since technological advances have been made, it only makes sense to program our devices so that they are able to understand our human language. In the world of computers, human language is called Natural Language.
Natural Language Processing uses spam filters. This is a commonly used defense mechanism much needed to identify spam messages and emails. We all receive tonnes of emails that we do not want to reply or might pose danger to our security. It becomes an uphill task to identify the futile emails from the ones we need to check. Well, these emails can be muted, sort of, with NLP. With the concept of false-positives and false-negatives, NLP is able to identify and extract meaning from strings of texts. Bayesian spam filtering is the popularly used technique that calculates the probability of a message being spam based on its contents.
Applications of Natural Language Processing
How will NLP shape the future? Find out more about this branch of Artificial Intelligence research and applications of…
Machine Translation: As the name makes its utilization obvious, natural language processing can be engaged in translation on the web. Data is extensive on the internet. People from different regions are able to access it from any part of the world. With this diversity in the number of users speaking and understanding different languages, NLP helps with the translation of those languages into their native languages. Google is the flag bearer of this along with many other companies using NLP for machine translation. This comes with its own set of challenges. The biggest challenge is to retain the original meaning of the translated text.
Summarization: NLP can be used in summarization of text to avoid the overload of information on the internet. A viral trend that is slowly taking over with its ability to summarize large chunk of text or document into a meaningful gist. This is an uphill task if you look at it properly. Extraction of the correct meaning from a long string of text poses many challenges. This is a useful technique that can help companies in understanding the sentiments behind the huge chunk of data they gather from their products and services. NLP can definitely change the way the market works.
If you have ever used Siri on iOS or any other digital assistant then you will definitely know what purpose NLP solves in ‘answering questions’. A QA application is a system capable of logically answering a valid human request. NLP has the capability to understand the human languages either in text-only format or spoken dialogue. This technology is still in the development phase as of now, but can still be seen widely used everywhere in for form of Siri, Ok Google, Amazon Echo Dot and chat boxes.
Well, these are pretty much the major uses of Natural Language Processing that we see and use. It is still a very technology extensively growing.
The Natural Language Processing market is predicted to reach $22.3 billion by 2025. You can master the skills to get computers to understand, process, and manipulate human language. Build models on real data, and get hands-on experience with sentiment analysis, machine translation, and more.
Enroll in Udacity’s Nanodegree program today and get the best skills on Natural Language Processing today!