https://github.com/harmanveer-2546/nlp
Natural Language Processing (NLP) is the sub field of computer science especially Artificial Intelligence (AI) that is concerned about enabling computers to understand and process human language.
https://github.com/harmanveer-2546/nlp
documentation natural-language-processing nlp-machine-learning nltk-python python
Last synced: 8 months ago
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Natural Language Processing (NLP) is the sub field of computer science especially Artificial Intelligence (AI) that is concerned about enabling computers to understand and process human language.
- Host: GitHub
- URL: https://github.com/harmanveer-2546/nlp
- Owner: harmanveer-2546
- Created: 2024-05-27T09:37:20.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-05-27T09:59:08.000Z (over 1 year ago)
- Last Synced: 2025-01-11T14:48:45.340Z (9 months ago)
- Topics: documentation, natural-language-processing, nlp-machine-learning, nltk-python, python
- Homepage:
- Size: 3.11 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
## NLP
The meaning of NLP is Natural Language Processing (NLP) which is a fascinating and rapidly evolving field that intersects computer science, artificial intelligence, and linguistics. NLP focuses on the interaction between computers and human language, enabling machines to understand, interpret, and generate human language in a way that is both meaningful and useful. With the increasing volume of text data generated every day, from social media posts to research articles, NLP has become an essential tool for extracting valuable insights and automating various tasks.
Natural language processing (NLP) is a machine learning technology that gives computers the ability to interpret, manipulate, and comprehend human language. Organizations today have large volumes of voice and text data from various communication channels like emails, text messages, social media newsfeeds, video, audio, and more. They use NLP software to automatically process this data, analyze the intent or sentiment in the message, and respond in real time to human communication.
### Why is NLP important?
Natural language processing (NLP) is critical to fully and efficiently analyze text and speech data. It can work through the differences in dialects, slang, and grammatical irregularities typical in day-to-day conversations.
### Companies use it for several automated tasks, such as to:
• Process, analyze, and archive large documents
• Analyze customer feedback or call center recordings
• Run chatbots for automated customer service
• Answer who-what-when-where questions
• Classify and extract text
You can also integrate NLP in customer-facing applications to communicate more effectively with customers. For example, a chatbot analyzes and sorts customer queries, responding automatically to common questions and redirecting complex queries to customer support. This automation helps reduce costs, saves agents from spending time on redundant queries, and improves customer satisfaction.