What is Natural Language Processing?
Natural Language Processing (NLP) is a field of artificial intelligence that focuses on enabling computers to understand and process human language. It bridges the gap between human communication and machine comprehension.
Essentially, NLP allows computers to read, understand, interpret, and generate human language, similar to how humans do it.
Key Concepts in NLP
Here are some crucial concepts within NLP:
- Tokenization: Breaking down text into individual units (words, punctuation).
- Part-of-Speech (POS) Tagging: Identifying the grammatical role of each word (noun, verb, adjective, etc.).
- Named Entity Recognition (NER): Identifying and classifying named entities (people, organizations, locations).
- Sentiment Analysis: Determining the emotional tone expressed in text.
- Machine Translation: Converting text from one language to another.
- Word Embeddings (Word2Vec, GloVe): Representing words as numerical vectors, capturing semantic relationships.
Example Code - Sentiment Analysis (Python)
import nltk
from nltk.sentiment.vader import SentimentIntensityAnalyzer
nltk.download('vader_lexicon')
analyzer = SentimentIntensityAnalyzer()
text = "This movie was absolutely amazing! I loved it."
scores = analyzer.polarity_scores(text)
print(scores)
# {'neg': 0.0, 'neu': 0.45, 'pos': 0.55, 'compound': 0.86}