Natural Language Processing

Natural Language Processing (NLP) is a branch of artificial intelligence that gives machines the ability to read, interpret, and generate human language - bridging the gap between how humans communicate and how computers process information.

Core Tasks in NLP

• Tokenization - splitting text into words or sentences
• Part-of-speech tagging - labeling words as nouns, verbs, adjectives, and so on
• Named entity recognition - identifying names of people, places, and organizations
• Sentiment analysis - determining whether text expresses a positive, negative, or neutral tone
• Machine translation - converting text from one language to another

A Typical NLP Pipeline

import re

text = "Uncodemy's Data Science course is amazing!"
cleaned = re.sub(r"[^a-zA-Z\s]", "", text).lower()
tokens = cleaned.split()
print(tokens)
# ['uncodemys', 'data', 'science', 'course', 'is', 'amazing']

Real-World Applications

NLP powers chatbots and virtual assistants, search engines, spam filters, auto-complete and grammar checkers, and large-scale customer feedback analysis.