Some of the common tasks of NLP include:

• Machine TRANSLATION: This helps in translating a given piece of text from one language to another.
• Text Summarization: Based on a large corpus, this is used to give a short summary that gives an idea of the entire text in the document.
• Language Modeling: Based on the history of previous words, this helps uncover what the further sentence will look like. A good example of this is the auto-complete sentences feature in Gmail.
• Topic Modelling: This helps uncover the topical structure of a large COLLECTION of documents. This indicates what topic a piece of text is actually about.
• QUESTION Answering: This helps prepare answers automatically based on a corpus of text, and on a question that is posed.
• Conversational Agent: These are basically voice assistants that we commonly see such as Alexa, Siri, Google Assistant, Cortana, etc.
• Information Retrieval: This helps in fetching RELEVANT documents based on a user’s search query.
• Information Extraction: This is the task of extracting relevant pieces of information from a given text, such as calendar events from emails.
• Text Classification: This is used to create a bucket of categories of a given text, based on its content. This is used in a wide VARIETY of AI-based applications such as sentiment analysis and spam detection.

Common NLP Tasks in order of Difficulty