NLP Introduction & Applications

 Natural Language Processing (NLP):

Natural language refers to the language used by humans to communicate with each other. This communication can be verbal or textual. For instance, face-to-face conversations, tweets, blogs, emails, websites, SMS messages, all comes under natural language.

Natural language is an incredibly important thing for computers to understand for a few reasons (among others):

• It can be viewed as a source of huge amount of data, and if processed intelligently can yield useful information.
• It can be used to allow computers to better communicate with humans.

However, unlike humans, computers cannot easily comprehend natural language. Sophisticated techniques and methods are required to translate natural language.

Natural language processing is a field of AI and computer science, that gives machines an ability to understand human language better and assist in language related tasks.

According to industry estimates, more than 80% of the data being generated in unstructured format, may be in the form of text, image, audio, video, etc. A few examples include- posts/tweets on social media, chat conversations, news, blogs, product or service reviews of E-commerce and patient records in health care sector.

Structured data: The elements in data, organized in a pre-defined format, like rows and columns( Excel-file).

Unstructured data: The elements in data are not organized in pre-defined form.

In order to produce significant and actionable insights from text data, we use Natural language processing coupled with machine learning and deep learning.

Applications of NLP:

• Information extraction
• Text summarization
• Text classification
• Text similarity
• Voice recognition
• Language translation
• Chat bots

Information extraction:

Information extraction is like we want retrieve the information from the whole. For example anything we search in browser, we will get related information.

Text summarization:

Text summarization will give us summary or verdict of the whole story. For example movie reviews verdict.

Text classification:

Classifying the text on the basis of categories. For example, news channel home page is categories as Sports, Political, Science & Technology, Health, Entertainment and etc.

Text similarity:

Text similarity is like finding similar kind of text. For instance, finding correct employee from the resume by applying text similarity with job description.

Voice recognition:

We have Voice assistance like google, Siri, and etc

Language translation:

We can translate any language from one language to another.

Chat bots:

Chat bots are nothing but making conversation between human and machine.  You may see it in some websites, a message will pop-up with greetings and try to make conversation to help you.