Machine Learning
Natural Language Processing :)
What is NLP??
Natural Language Processing or NLP is a field of Artificial Intelligence that gives the machines the ability to read, understand and derive meaning from human languages.
Using NLP, machines can make sense of unstructured online data so that we can gain valuable insights.
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Once a fantasy of science fiction movies, the ability of machines to interpret human language is now at the core of many applications that we use every day – from translation software, chatbots, spam filters, and search engines, to grammar checking software, voice assistants, and social media monitoring tools.
Why NLP is necessary??
Tons of data is generating through mails, tweets, web searches every day, However most of the digital data is unstructured - Making it hard for machines to understand, analyze and extract meaningful information.
NLP plays very important role in structuring data. Suppose you want to analyze sentiment of thousands of tweets and find out which ones refer to your product in a positive or negative way. Thanks to NLP, machines can automate this process quickly and effectively.
How does NLP work??
When we read text or see something, our brain decodes series of words. Those human abilities allows us to understand the language, NLP tries to simulate and convey same things to machine.
NLP works by breaking down words into their simplest form and identifying patterns, rules, and relationships between them.
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NLP makes use of a combination of linguistics and computer science. Linguistics is used to understand the structure and meaning of a text by analyzing different aspects like syntax, semantics, pragmatics, and morphology.Then, computer science transform this knowledge into some rules or machine learning algorithm that can solve specific problems.
NLP Techniques !!
Tokenization
It is process of splitting a string, text into a list of tokens.
Part of speech tagging
It is a task of labeling each word in a sentence with its appropriate part of speech.
Lemmatization &Â Stemming
Process of reducing a word to its word stem or base form.
Lemmatization & Stemming are two similar NLP tasks that consist of reducing words to their base form so that they can be analyzed by their common root.
NLP Applications
Sentiment Analysis
It is the interpretation and classification of emotions (positive, negative and neutral) within text data using text analysis techniques. Sentiment analysis allows businesses to identify customer sentiment toward products, brands or services in online conversations and feedback.
Chatbots
Chatbots are becoming common and a powerful tool to engage online visitors by interacting with them in their natural language. Earlier, websites used to have live chats where agents would do conversations with the online visitor and answer their questions. But obviously it is not an good idea to sit in front of PC and answer the questions 24/7.Here comes the chatbots, solves the issue by being active around the clock and engage the website visitors without any human assistance.
Some other use-cases of NLP
