intermediate·10 min

Natural Language Processing

NLP enables computers to understand, interpret, and generate human language — the foundation of chatbots, translation, and more.

🧑For teens & curious minds
Natural Language Processing combines linguistics and machine learning to enable computers to process and analyze text and speech data. Tasks include sentiment analysis, named entity recognition, machine translation, question answering, and text generation.
💡Visual Analogy

NLP is like having a translator who not only converts words between languages but also understands tone, emotion, context, and cultural nuance.

Key Terms

Tokenization:Breaking text into words or subwords for processing.
Sentiment Analysis:Determining whether text is positive, negative, or neutral.
Named Entity Recognition:Identifying names of people, places, and organizations in text.

🎯 Fun Facts

  • •Google processes over 8.5 billion search queries daily using NLP.
  • •Modern NLP models can detect sarcasm, humor, and irony in text.
  • •NLP is used to monitor social media in real time for health crisis signals.
  • •The first NLP program, ELIZA, was created in 1966 and fooled people into thinking it was human.

Real World Examples

  • ✓Google Search understanding your query
  • ✓Real-time language translation
  • ✓Customer review sentiment analysis
  • ✓Email autocomplete
  • ✓Voice assistants