NLP's algorithms recognise texts and can edit, summarise and classify them. NLP is characterized as a difficult problem in computer science. Human language is generally neither precise nor plainly spoken. Moreover, in terms of data science, it is unstructured text data. Understanding human language means not just recognizing the words, but also perceiving the ideas, and concepts, and how they’re linked together to create meaning., analytics etc.Businesses are interested in text data because it contains information relating to marketing media, pricing playbooks, product documentation, business contracts, etc. Natural processing language applies techniques to extract patterns in textual data from large datasets.Thus in this session we try to understand NLP and its uses in automation.Use cases include: chatbot, sentiment analysis, text mining Key question's we would answer: What is NLP?Why NLP?Approaches?Valid-use cases for NLP in Software Development and automation?Future?
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