Day 201 of 365: Introduction to POS Tagging and Named Entity Recognition (NER) 🚀📚✏️🚀

Hey, Tagger!

Welcome to Day 201 of our #365DaysOfDataScience journey! 🎉

Today, we’re diving into two fundamental NLP techniques that help transform text into structured information: Part-of-Speech (POS) tagging and Named Entity Recognition (NER).

🔑 What We’ll Be Exploring Today:

- POS Tagging:

   - Learn about the importance of POS tagging and how it helps identify the grammatical structure of sentences.

- Named Entity Recognition (NER):

   - Discover how NER extracts important entities (like names, locations, and dates) from text, providing valuable insights in NLP tasks.

📚 Learning Resources:

- Read:

   - POS tagging and NER basics from the `spaCy` documentation.

✏️ Today’s Task:

- Hands-On:

   - Use `spaCy` to perform POS tagging and NER on a text dataset. Explore how words are tagged and which entities get recognized.

Let’s unlock some structured insights from unstructured text! This will be fun—especially seeing how simple models can pull out key info like people, places, and more from raw data!

Happy Learning & See You Soon!

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