Natural Language Processing (NLP)
Natural Language Processing (NLP) is a branch of artificial intelligence (AI) that enables computers to understand, interpret, and generate human language. It combines linguistics, machine learning (ML), and deep learning to process text and speech.
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Key Components of NLP
1. Text Processing
- Tokenization: Splitting text into words or sentences.
- Lemmatization & Stemming: Reducing words to their root form.
- Stopword Removal: Filtering out common words like "the" and "is".
-Part-of-Speech (POS) Tagging: Identifying nouns, verbs, adjectives, etc.
2. Semantic Analysis
- Named Entity Recognition (NER): Identifying names, places, dates, etc.
- Sentiment Analysis: Detecting emotions in text (positive, negative, neutral).
- Word Sense Disambiguation: Understanding the meaning of words based on context.
3. Speech Processing
- Speech-to-Text (STT): Converting spoken words into text.
- Text-to-Speech (TTS): Converting text into spoken audio.
4. Machine Translation
- Example: Google Translate, DeepL.
5. Text Generation
- Example: AI chatbots, content writing (GPT, LLaMA, Claude).
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Popular NLP Models & Tools:
Transformers: GPT-4, LLaMA, BERT, T5, Mistral
Libraries: NLTK, spaCy, Hugging Face, OpenAI API
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