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Natural Language Processing

                 NLP  is  a  field  of  computer  science  and  AI  that  focuses  on  training  machines  to  understand  and  process  human
                 languages in both written and spoken forms, just like humans do. An NLP-trained model aims to "understand" the
                 content of documents, including slang, sarcasm, inner meanings, and contextual definitions of the language used. The
                 best examples of NLP are Google Assistant, Microsoft’s Cortana, Amazon’s Alexa, and Apple’s Siri.
                 Here are some examples of how NLP enriches your life, without you noticing it:
                    • Autocomplete recommends the next word.
                    • In the Google search field, predictive typing suggests the next/remaining words in the sentence.
                    • Spell checks eliminate misspellings, errors, and spellings that are stylistically inappropriate.
                    • Grammar  checkers  ensure  that  you  use proper  punctuation  and  warn  you  if you  use the  incorrect  article or
                   proposition. For example, Grammarly.
                    • Converts spoken language into written text.
                    • Companies use NLP to perform sentiment analysis to gauge public opinion on social media.
                 NLP consists of Natural Language Understanding (NLU) and Natural Language Generation (NLG).

                                                                                Syntactic parsing


                                                                               Semantic analysis
                                                       Natural Language
                                            Natural Language Processing     Named entity recognition
                                                        Understanding



                                                                               Sentiment analysis


                                                                                 Text planning


                                                       Natural Language     Date-to-text transformation
                                                          Generation

                                                                               Surface realisation

                 Let us understand what these terms mean:
                   • Natural Language Understanding (NLU): NLU is a subfield of NLP that focuses on comprehending the meaning
                   of human language. It involves analysing text and speech to extract information, intent, and sentiment. NLU helps
                   computers understand what the language actually means. Imagine finding a specific book in the library that provides
                   deep insights into a topic. For instance, NLU is used in spam filters to determine whether an email is legitimate or spam.
                    • Natural Language Generation (NLG): NLG is another subfield of NLP, but instead of understanding, it focuses on
                   generating human language. It takes structured data as input and converts it into coherent and readable text or
                   speech. Think of NLG as writing a new book based on the information collected from the library. A real-life example
                   of NLG is automatic report generation, where software creates financial reports based on data from spreadsheets.

                        Computer Vision


                 Computer Vision is like giving computers the ability to see and understand the world through digital images and
                 videos, similar to how humans use their eyes to perceive their surroundings. In this domain, computers analyse visual
                 information from images and videos to recognise objects, understand scenes, and make decisions based on what
                 they "see".

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