01-embeddings

Embeddings for NLP

This repository contains a Jupyter Notebook demonstrating practical implementations of embeddings in Natural Language Processing (NLP). The notebook (embeddings-for-nlp.ipynb) provides hands-on examples and explanations of embedding concepts.

Overview

Embeddings are fundamental to modern NLP, allowing us to represent words and tokens as dense vectors that capture semantic relationships. This notebook provides a practical exploration of embedding concepts, from basic implementations to more advanced techniques.

Contents

The notebook covers:

• Basic concepts of word embeddings
• Implementation of embedding layers
• Techniques for working with embeddings
• Practical examples and visualizations

Requirements

• Python 3.12+
• PyTorch
• NumPy

Getting Started

1. Clone this repository
2. Install the required dependencies
3. Open embeddings-for-nlp.ipynb in Jupyter Notebook