Natural Language Processing (NLP) with Python 🧠

Welcome to the NLP Python Tutorial! This guide will walk you through the essentials of working with text data using Python. 🚀

Why Python for NLP?

Python is a popular choice for NLP due to its:

• 📚 Rich ecosystem of libraries (e.g., spaCy, NLTK, Transformers)
• 🧰 Simple syntax and readability
• 🌐 Strong community support

Key NLP Libraries in Python

Here are some widely used tools:

1. spaCy 🐍

   • Fast and efficient library for processing text
   • Learn more →

2. NLTK 🦜

   • Great for beginners and educational purposes
   • Explore examples →

3. Transformers 🧠

   • Implements state-of-the-art models like BERT and GPT
   • Check documentation →

Simple NLP Example

import spacy

nlp = spacy.load("en_core_web_sm")
doc = nlp("Python is amazing for NLP tasks!")

for token in doc:
    print(f"{token.text} → {token.pos_}")

Next Steps

Ready to dive deeper? Explore these resources:

• Tokenization & Sentiment Analysis →
• Advanced Models with Transformers →
• NLP Workflow Diagram →