Natural Language Processing (NLP) is a subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human (natural) languages. As such, NLP is related to the area of human-computer interaction. Many challenges in NLP involve natural language understanding, that is, enabling computers to derive meaning from human or natural language input.
Key Concepts in NLP
- Tokenization: The process of breaking text down into words, phrases, symbols, or other meaningful elements called tokens.
- Part-of-Speech Tagging: Assigning parts of speech to each word in a sentence, such as noun, verb, adjective, etc.
- Named Entity Recognition (NER): Identifying entities in text such as names, places, organizations, etc.
- Sentiment Analysis: Determining the sentiment or emotional tone behind a body of text.
NLP Applications
- Search Engines: Improving search results by understanding the intent behind queries.
- Chatbots: Automating customer service and providing personalized experiences.
- Machine Translation: Translating text from one language to another.
- Text Summarization: Generating a concise summary of a longer text.
Learn More
To dive deeper into the world of NLP, consider exploring our Introduction to Machine Learning course. This will provide you with a solid foundation in the principles and techniques of machine learning, which are essential for understanding NLP.
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