LLM Foundations: Get started with tokenization
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Get started with Large Language Model (LLM) foundations and tokenization. Learn how tokenization is a critical step in NLP and machine learning, and explore techniques for breaking down text data into meaningful components for model training.
At a Glance
Tokenization is a preprocessing technique in natural language processing (NLP) that converts text to structured data so a computer can understand human language. It breaks down unstructured text data into smaller units called tokens. A single token can range from a single character or individual word to much larger textual units.
This project is based on the IBM Developer tutorial Tokenizing text in Python, by Jacob Murel (Ph.D).
A Look at the Project Ahead
- Introduction to tokenization concepts in text processing.
- Exploring different methods and libraries for tokenizing text in Python.
- Practical examples and exercises to apply tokenization techniques.
What You’ll Need
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