According to industry estimates, only 21% of the available data is present in structured form. Data is being generated as we speak, as we tweet, with every minute. Majority of this data exists in the textual form, which is highly unstructured in nature.
Few notorious examples include – tweets / posts on social media, user to user chat conversations, news, blogs and articles, product or services reviews and patient records in the healthcare sector. A few recent ones include chat bots and other voice driven bots.
Despite having high dimension data, the information present in it is not directly accessible unless it is processed (read and understood) manually or analyzed by an automated system.
In order to produce significant and actionable insights from text data, it is important to get acquainted with the techniques and principles of Natural Language Processing (NLP).
So, if you plan to create chat bots this year, or you want to use the power of unstructured text, this guide is the right starting point. This guide unearths the concepts of natural language processing, its techniques and implementation. The aim of the article is to teach the concepts of natural language processing and apply it on real data set.
Humans are social animals and language is our primary tool to communicate with society. But, what if machines could understand our language and then act accordingly? Natural Language Processing (NLP) is the science of teaching machines how to understand the language we humans speak and write.
Natural Language Processing is one of the principal areas of Artificial Intelligence. NLP plays a critical role in many intelligent applications such as automated chat bots, article summarizers, multilingual translation and opinion identification from data. Every industry which exploits NLP to make sense of unstructured text data, not just demands accuracy, but also swiftness in obtaining results.
Natural Language Processing is a capacious field, some of the tasks in nlp are – text classification, entity detection, machine translation, question answering, and concept identification.