Natural Language Processing

What is NLP?

Natural Language Processing (NLP) is the branch of AI that helps computers understand, interpret, and generate human language. It's what powers chatbots, translation services, and voice assistants.

NLP Tasks

• Text Classification — Is this email spam or not?
• Sentiment Analysis — Is this review positive or negative?
• Named Entity Recognition — Finding names, dates, places in text
• Machine Translation — Translating between languages
• Text Generation — Writing human-like text
• Question Answering — Answering questions from text

How NLP Works

Traditional NLP used rules and statistics. Modern NLP uses transformers — neural networks that process all words in context simultaneously.

Key Concepts

1. Tokenization — Splitting text into words or subwords
2. Embeddings — Converting words to numbers (vectors) that capture meaning
3. Attention — Understanding which words relate to each other
4. Context — The same word can mean different things ("bank" = river vs. financial)

Try It: Sentiment Analysis Demo

Below is a real machine learning model running in your browser! It analyzes the sentiment of any text you enter:

The model classifies text as positive or negative using a distilled BERT model running entirely in your browser via transformers.js. No data is sent to any server.

How the Demo Works

1. A pre-trained DistilBERT model is loaded into your browser
2. Your text is tokenized into subwords
3. The model processes the tokens through its neural network
4. It outputs a sentiment prediction with confidence scores

Python Libraries for NLP

When you're ready to build real NLP applications in Python:

• spaCy — Industrial-strength NLP
• NLTK — Educational NLP toolkit
• Transformers (Hugging Face) — State-of-the-art models
• TextBlob — Simple, beginner-friendly NLP