A personal learning project focused on implementing foundational Natural Language Processing (NLP) models from scratch using NumPy.
Models Included:
- Word2Vec (Skip-gram)
- Vanilla Recurrent Neural Network (RNN)
Purpose: The main goal of this project is educational. It serves as a hands-on exercise to:
- Solidify understanding of fundamental NLP algorithms.
- Strengthen knowledge of the underlying mathematics.
- Translate theoretical concepts, such as those taught in Stanford's CS224N, into practical code.